Ian McCrabb
Ian McCrabb is the founder and managing director of Systemik (systemiksolutions.com), a Sydney based IT consulting group focused on open-source digital humanities platforms and research sites.
Since its establishment in 1994, he has led the design, development and commercialization of consulting methodologies, web technologies and content transformation services: adapting the organizations operational models to map to rapidly evolving web content management platforms and strategies across manufacturing, finance and the public sector. Systemik currently supports a portfolio of humanities research platforms, web content management solutions and associated consulting and support services. Our solutions are clustered around content transformation and relationship graphing with integrated models for text analysis, mapping and image annotation. Systemik forte is the realisation of elite scholarship as immersive and engaging research experiences.
Ian is the founder and director of Prakaś Foundation (prakas.org), a non-profit association established in 2005 to support digital scholarship in Buddhist studies and Sanskritic languages. Prakaś provides funding, strategic planning and program management for platform developments.
Ian completed his MA in Sanskrit and Buddhist Studies at the University of Sydney in 2010. His 2021 PhD dissertation 'Buddha Bodies and the Benefits of Relic Establishment: Insights from a Digital Framework for the Analysis of Formulaic Sequences in Gāndhārī Relic Inscriptions' continued his focus on methodologies for the analysis of donative inscriptions and characterization of the ritual practices and religious significance of relic establishment in Gandhāra.
Ian was analyst/designer and project manager on the READ project, an open-source research environment for ancient Sanskrit and Prakrit texts. Ian designed READ Workbench, a corpus collaboration framework for philological research, and Image Annotation Workbench, a collaboration framework for scholarly annotation of images of manuscripts, inscriptions and items of art historical significance.
Phone: 0407337588
Address: Sydney, New South Wales, Australia
Since its establishment in 1994, he has led the design, development and commercialization of consulting methodologies, web technologies and content transformation services: adapting the organizations operational models to map to rapidly evolving web content management platforms and strategies across manufacturing, finance and the public sector. Systemik currently supports a portfolio of humanities research platforms, web content management solutions and associated consulting and support services. Our solutions are clustered around content transformation and relationship graphing with integrated models for text analysis, mapping and image annotation. Systemik forte is the realisation of elite scholarship as immersive and engaging research experiences.
Ian is the founder and director of Prakaś Foundation (prakas.org), a non-profit association established in 2005 to support digital scholarship in Buddhist studies and Sanskritic languages. Prakaś provides funding, strategic planning and program management for platform developments.
Ian completed his MA in Sanskrit and Buddhist Studies at the University of Sydney in 2010. His 2021 PhD dissertation 'Buddha Bodies and the Benefits of Relic Establishment: Insights from a Digital Framework for the Analysis of Formulaic Sequences in Gāndhārī Relic Inscriptions' continued his focus on methodologies for the analysis of donative inscriptions and characterization of the ritual practices and religious significance of relic establishment in Gandhāra.
Ian was analyst/designer and project manager on the READ project, an open-source research environment for ancient Sanskrit and Prakrit texts. Ian designed READ Workbench, a corpus collaboration framework for philological research, and Image Annotation Workbench, a collaboration framework for scholarly annotation of images of manuscripts, inscriptions and items of art historical significance.
Phone: 0407337588
Address: Sydney, New South Wales, Australia
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The research proposition—that new insights might be accessible through pattern analysis of formulaic sequences—indicated an ambitious infrastructure proposition. The dissertation is a cascading program of projects to develop the foundational models, supporting platforms and enabling methodologies required to implement formulae structures and formula analysis across the corpus. The dissertation arc returns, equipped with that infrastructure, to the characterisation of the ritual architecture of relic inscriptions.
The design and development of a platform of the scale of READ—the philological platform developed in consortium—required the deployment of a research consulting framework. The methodologies, toolkits, and defining role of a research consultant, were exercised in a suite of consulting solutions and corpus projects.
The inherent constraints of a conventional centralised architecture necessitated the design of a corpus development framework. The encapsulation of the TextBase methodology in READ Workbench—an Open SaaS portal—crystalizes a sustainable solution architecture for collaborative corpus development in the philological domain.
The infrastructure suite was deployed in the development of a reconstituted relic inscriptions corpus, and the implementation of a synthesized syntactic and semantic formula ontology. The detailed analysis of formulae type, alignment and inflection produced new translations of critical passages, a ritual architecture hypothesis and a novel view of the ontological status of relics and bodies of the Buddha grounded in Gandhāran Buddhism.
The content of the features module of the site provides an outline of functionality organised by feature and constituent feature. The content of the workflow module of the site elaborates on the workflows established in a corpus platform mapping exercise with a comprehensive suite of TextBase methodology documentation: workflow, process, procedure and standards. This documentation suite integrates both Workbench and READ processes within an end-to-end corpus development workflow arc.
Workbench’s three facets – configuration services, self-service portal, and corpus development workflows – provide a scalable implementation framework.
Configuration services support the provision and management of multiple READ installations; each with project and language-specific configurations and institutional branding.
Self-service portal features enable researchers to establish and manage their projects without technical support. Comprehensive sharing capability supports flexible collaboration for editing, analysis, and review.
Corpus development workflows support researchers through the entire project arc of importing, editing, analysing and digitally publishing research outputs. Workbench instantiates a corpus development methodology, TextBase, to address scalability, project management and sustainability in collaborative projects.
Digital repatriation aims to expand engagement with these culturally significant items which have largely been limited to research specialists. The project uses open-source technologies to make these items, and the scholarly knowledge associated with them, accessible to general academic and interest communities.
The strategy is comprised of three integrated frameworks:
-the core research framework supports the development of scholarly digital editions of manuscripts and inscriptions,
-the publishing framework frames and contextualizes these editions for engagement with both the wider scholarly community and general interest and heritage communities,
-the governance framework manages policy and attribution on the range of digital artefacts and research outputs contributed in collaborative digital publications.
The consortium was formed to support and extend the existing research and publishing frameworks, and to develop a governance framework as an essential component of an integrated repatriation strategy.
The presentation will focus on the models, platforms and methodologies which constitute the research and publishing frameworks and will demonstrate pilot instantiations of digital repatriation of manuscripts, inscriptions and Gandhāran art.
The platforms constitute this framework are
1. READ: an open-source environment for epigraphic and manuscript research which supports the transcription, research, understanding, analysis and publishing of scholarly editions and studies. Developed in consortium by LMU-Munich, Prakaś, University of Lausanne, University of Sydney and University of Washington-Seattle
2. READ Workbench: a web portal which supports the integration and management of researchers, resources, tools and processes in the collaborative development and publishing of textual corpora. Developed by Prakaś.
Outcomes to date:
• Gandhāran Buddhist Texts site: https://gandhari-texts.sydney.edu.au/ which includes both manuscript and inscriptional collections, e.g. Robert Senior Manuscripts: https://gandhari-texts.sydney.edu.au/collections/robert-senior-collection/
• The digital Journal of Gandhāran Buddhist Texts: https://gandhari-texts.sydney.edu.au/text/a%e1%b9%87atvalak%e1%b9%a3a%e1%b9%87a-sutra/ that will enable the publication in a more timely fashion of the very large number of new Gandhari manuscripts and inscriptions now available.
A new initiative is the integration of text with 3D models: https://gandhari-texts.sydney.edu.au/text/theodotus-swat-steatite-miniature-stupa/.
In conjunction with Gandharan art historians, the platforms have been extended to support new avenues for scholarship in the integration of text, 3D models and art historical analysis. The initial project aims to create a corpus of inscribed Buddha images and a corpus of inscribed reliquaries for which pilot funding is being sought.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
The READ project commenced in 2013 with development support from a consortium of institutions (Ludwig Maximillian University, the University of Washington, the University of Lausanne and the University of Sydney) involved in the study and publication of ancient Buddhist documents preserved in the Gāndhārī language that originate from Afghanistan and Pakistan. READ version 1.1 was completed in March 2016.
READ has been designed as a comprehensive multi‐user research workbench and publishing platform for ancient Sanskrit and Prakrit texts.
The design approach has been to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle is atomization of data to its smallest indivisible components and the linking and sequencing of these entities. This approach allows for attribution and annotation at every entity to record scholarly contribution at the finest level of granularity.
A great deal of work has been undertaken on the design and development of a comprehensive, extensible and configurable system ontology. The ontology provides standardized terms for both Physical and Textual domains; everything from object shapes and types to grammatical categories such as declension and conjugation values. These standard terms manifest as constraints within the system and ensure data consistency and quality.
READ is based on open source software and built to open standards. It provides an extensible entity model and a published API for integration with related systems. The technology stack includes PostgreSQL with backend development in PHP and UI development using JQuery. Fundamental to the design of READ is support for the import and export of TEI. The method adopted is XSLT transformation to EpiDoc specifications of an XML rendition of stored data. Import is the same process in reverse. Whatever format existing transcriptions were developed in these can be consumed, elaborated upon, analyzed, and then published as research output in TEI.
In summary, READ has been designed to functions as:
• a linked repository of images, transcriptions, translations, metadata, commentary and bibliographic records,
• a content management system encompassing multi-user editing, maintenance and version control,
• a collaboration platform with comprehensive access and visibility control to support draft development, workgroup collaboration and public presentation,
• a research workbench with access to a dictionary, corpus of texts, catalogs, glossaries, concordances and bibliography
• a publishing platform for individual transcription renditions or full scholarly editions, both print-ready and online, and
The kernel of an integrated research network interfacing with related dictionaries, repositories of parallel texts, GIS, data visualization, image rendering and palaeographic analysis systems.
The research proposition—that new insights might be accessible through pattern analysis of formulaic sequences—indicated an ambitious infrastructure proposition. The dissertation is a cascading program of projects to develop the foundational models, supporting platforms and enabling methodologies required to implement formulae structures and formula analysis across the corpus. The dissertation arc returns, equipped with that infrastructure, to the characterisation of the ritual architecture of relic inscriptions.
The design and development of a platform of the scale of READ—the philological platform developed in consortium—required the deployment of a research consulting framework. The methodologies, toolkits, and defining role of a research consultant, were exercised in a suite of consulting solutions and corpus projects.
The inherent constraints of a conventional centralised architecture necessitated the design of a corpus development framework. The encapsulation of the TextBase methodology in READ Workbench—an Open SaaS portal—crystalizes a sustainable solution architecture for collaborative corpus development in the philological domain.
The infrastructure suite was deployed in the development of a reconstituted relic inscriptions corpus, and the implementation of a synthesized syntactic and semantic formula ontology. The detailed analysis of formulae type, alignment and inflection produced new translations of critical passages, a ritual architecture hypothesis and a novel view of the ontological status of relics and bodies of the Buddha grounded in Gandhāran Buddhism.
The content of the features module of the site provides an outline of functionality organised by feature and constituent feature. The content of the workflow module of the site elaborates on the workflows established in a corpus platform mapping exercise with a comprehensive suite of TextBase methodology documentation: workflow, process, procedure and standards. This documentation suite integrates both Workbench and READ processes within an end-to-end corpus development workflow arc.
Workbench’s three facets – configuration services, self-service portal, and corpus development workflows – provide a scalable implementation framework.
Configuration services support the provision and management of multiple READ installations; each with project and language-specific configurations and institutional branding.
Self-service portal features enable researchers to establish and manage their projects without technical support. Comprehensive sharing capability supports flexible collaboration for editing, analysis, and review.
Corpus development workflows support researchers through the entire project arc of importing, editing, analysing and digitally publishing research outputs. Workbench instantiates a corpus development methodology, TextBase, to address scalability, project management and sustainability in collaborative projects.
Digital repatriation aims to expand engagement with these culturally significant items which have largely been limited to research specialists. The project uses open-source technologies to make these items, and the scholarly knowledge associated with them, accessible to general academic and interest communities.
The strategy is comprised of three integrated frameworks:
-the core research framework supports the development of scholarly digital editions of manuscripts and inscriptions,
-the publishing framework frames and contextualizes these editions for engagement with both the wider scholarly community and general interest and heritage communities,
-the governance framework manages policy and attribution on the range of digital artefacts and research outputs contributed in collaborative digital publications.
The consortium was formed to support and extend the existing research and publishing frameworks, and to develop a governance framework as an essential component of an integrated repatriation strategy.
The presentation will focus on the models, platforms and methodologies which constitute the research and publishing frameworks and will demonstrate pilot instantiations of digital repatriation of manuscripts, inscriptions and Gandhāran art.
The platforms constitute this framework are
1. READ: an open-source environment for epigraphic and manuscript research which supports the transcription, research, understanding, analysis and publishing of scholarly editions and studies. Developed in consortium by LMU-Munich, Prakaś, University of Lausanne, University of Sydney and University of Washington-Seattle
2. READ Workbench: a web portal which supports the integration and management of researchers, resources, tools and processes in the collaborative development and publishing of textual corpora. Developed by Prakaś.
Outcomes to date:
• Gandhāran Buddhist Texts site: https://gandhari-texts.sydney.edu.au/ which includes both manuscript and inscriptional collections, e.g. Robert Senior Manuscripts: https://gandhari-texts.sydney.edu.au/collections/robert-senior-collection/
• The digital Journal of Gandhāran Buddhist Texts: https://gandhari-texts.sydney.edu.au/text/a%e1%b9%87atvalak%e1%b9%a3a%e1%b9%87a-sutra/ that will enable the publication in a more timely fashion of the very large number of new Gandhari manuscripts and inscriptions now available.
A new initiative is the integration of text with 3D models: https://gandhari-texts.sydney.edu.au/text/theodotus-swat-steatite-miniature-stupa/.
In conjunction with Gandharan art historians, the platforms have been extended to support new avenues for scholarship in the integration of text, 3D models and art historical analysis. The initial project aims to create a corpus of inscribed Buddha images and a corpus of inscribed reliquaries for which pilot funding is being sought.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
READ has been developed as a comprehensive multi-user platform for the transcription, translation and analysis of ancient Sanskrit, Gāndhārī, Pali and other Prakrit texts: manuscripts, inscriptions, coins and other documents. It is based on open source software (Postgres, PHP and JQuery), supports the TEI standard and provides an API for integration with related systems. READ is positioned as a research environment, complementary to existing textual repositories and integrated with existing dictionaries. Existing transcriptions can be imported, elaborated upon, analyzed, and then published as research output in standards-based formats. The defining innovation of READ is atomization to a semantically linked network of objects; a paradigm shift in data structure from strings of marked-up text to aggregates of linked objects. READ supports the alpha syllabary languages and is currently being prototyped on a range of other language groups.
The underlying design and entity model was presented at both the Digital Humanities conference in 2015 and the 2016 Australian Digital Humanities Conference. READ has been publicly released and is supporting a wide range of corpus development projects. Whilst this presentation will follow on to briefly precis the range of research projects currently supported by READ, the focus will be on a related platform. READ Workbench (Workbench) is a server portal hosted at the University of Sydney since 2016 to ‘harness’ READ. Developed using the same technology stack as READ, it is a comprehensive management framework and implementation platform to support the integration of people and processes in the collaborative development, maintenance and publishing of textual corpora.
The design of Workbench evolved organically as the implementation requirements of READ expanded from a single researcher working on a single text, to the capacity to support multiple projects, each with a team of researchers collaborating on the development of an integrated corpora, with widely divergent research objectives. The fundamental objective was to design a supporting framework with which to address issues of scalability, project management and sustainability and to manage the balance between autonomy and collaboration in large scale projects. The approach adopted was to implement strategies, models and workflow patterns consistent with those applied in the IT consulting industry to digital content design, development and migration projects.
Workbench is a software as a service (SaaS) platform managing multiple READ installations, each with project and language specific configurations, supporting researcher collaborations across multiple institutions. Workbench currently supports multi institutional Gāndhārī, Sanskrit and Pali corpus development projects as well as a range of special collection and multi disciple collaborations. It provides a self-service portal for researchers to develop, maintain, manage and publish texts without requiring technical support or the mediation of a database administrator; critical to the longer-term sustainability of corpora projects. Workbench radically lowers the barrier to entry for research projects as neither funding nor configuration of software infrastructure is required.
Workbench’s three facets (configuration management, database management and corpus workflows) provide a scalable implementation architecture for READ and instantiate a comprehensive corpus development methodology. Whilst the configuration management services might be bracketed as conventional for a SaaS platform, database management is predicated upon an architectural innovation that enables researchers to build, share, manage, maintain and publish their own texts. The adoption of a single text/single database (TextBase) as the fundamental object of development, collaboration and portability is quite a departure from conventional models where a centralized administrator manages a single monolithic corpus database.
This TextBase architecture underpins a corpus development, analysis and publishing methodology that provides significant flexibility in terms of the iteration and synchronization of four fundamental workflows: text alignment, text cubing, analysis registration and text aggregation.
The text alignment workflow integrates image, text and model configuration data to automatically generate a database. This approach allows for the distribution of responsibility to specialists and integration of their research output to align the image and the transcription at syllable level to generate a ‘substrate’. Rather than requiring researchers to command exacting mark-up schemas, substrate databases can be automatically generated from Word processing and Spreadsheet inputs supported by templates, standards and sophisticated error reporting. Workbench enables each of the specialist roles to work independently and their contributions be separately managed and integrated, ameliorating project risk by minimizing dependencies and bottlenecks.
The text cubing workflow facilitates successive cloning and editing, from an initial reference substrate (the earliest edition from which subsequent editions might be considered to have been derived) through the various subsequent editions to the encapsulate the scholarly history of the text and the attribution and provenance of innovations. A contemporary researcher might clone and develop their own edition, adding new readings and interpretations predicated upon an homage to previous scholarship.
The analysis registration workflow synchronizes analysis data with an existing substrate. This approach allows a researcher to work independently and externally to READ in developing their own analysis ‘strata’ and then register that strata on a substrate. Grammatical analysis, translation, semantic, syntactic and structural analysis can all be independently developed and iteratively registered. Researchers from other disciplines can develop and register their own analysis (archaeological, historical etc.). Each stratum is registered on a particular substrate (an edition) of the text within a TextBase, is separately owned and attributed, and its visibility is controlled by the researcher registering it.
The text aggregation process allows individual researchers to work and innovate in private to the point where they elect to participate in research collaborations or their text is ready for publishing. A TextBase might be aggregated with others to form a ‘sequenced’ collection, a ‘mapped’ collection or a ‘merged’ corpus; a continuum expressing an increasing degree of synthesis and harmonization of analysis ontologies and methodological standards. Researchers may contribute their TextBase to any number of aggregates. This approach allows a researcher to align a TextBase with the analysis standards of an established corpus as a predicate to participation as a constituent of that merged aggregate. In parallel, that same TextBase might be mapped to the analysis ontology of an entirely different collection. The potential exists for the same TextBase substrate to manifest as a constituent of separate aggregates, with alternative configurations of registered analysis strata, supporting widely divergent (aggregate specific) research objectives; the emanation of multiple TextBase avatars.
The strategy adopted with Workbench was to design a solution architecture within which to reframe some of the ubiquitous issues in the conventional corpus development model; ownership, control, confidentiality, innovation, standardization, portability, resourcing and support. The critical innovation in maximizing development flexibility and in balancing autonomy and collaboration across the range of individual, collection and corpora development projects is the TextBase; the target of text alignment, the containment boundary for text cubing, the substrate for registration of analysis and the constituent aggregated.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
Whilst this presentation will briefly precis the range of research outputs currently supported by the platform, the focus will be on a related platform, READ Workbench (Workbench), developed at University of Sydney to ‘harness’ the deployment of READ.
Workbench is a comprehensive management framework that supports configuration management, user access and database management and automation of corpus development processes. Workbench manages an unlimited number of projects each with their own branding, subdomain and language configuration; Gāndhārī, Pali or Sanskrit.
The design approach with READ was to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle was atomization of data to its smallest indivisible components and the linking and sequencing of these entities up through scale. The same design approach has been taken with Workbench when modelling the integration of resources and processes in the collaborative development, maintenance and publishing of textual corpora.
The architecture adopted rests on the fundamental object being a single text/single database; a departure from the conventional corpus model of a monolithic database. This approach allows individual researchers to build, maintain and manage their own text database(s) independently, in private and without the requirement for a database administrator or technical support. Workbench acts as a self-service portal.
The adoption of a single text database model facilitates a range of automated import processes and provides significant flexibility in terms of corpus development and publishing methodologies. Rather than requiring researchers to command exacting mark-up schemas, databases can be automatically generated from separate text, image and metadata inputs based on familiar tools like Word and Excel. Workbench enables each of the specialist roles (paleographic, philological, lexical, analytical etc.) to work independently and their contributions be separately managed and integrated. This approach ameliorates project risk by minimizing dependencies and bottlenecks.
Once image and text have been aligned, additional strata of analysis can be integrated. Grammatical analysis and glossary development, translation, syntax and structural analysis can all be independently developed and automatically imported. Researchers from diverse disciplines (archaeological, historical etc.) can also contribute analysis strata to this substrate. Critically, each of these strata are separately owned and attributed and their visibility to others is controlled by the individual researcher.
Individual text databases may at any point be merged with other text databases to form flexible collections. This approach allows individual researchers to work and innovate in private to the point where there text is ready for publishing and at that point merge their text with a canonical corpus.
The READ project commenced in 2013 with development support from a consortium of institutions (Ludwig Maximillian University, the University of Washington, the University of Lausanne and the University of Sydney) involved in the study and publication of ancient Buddhist documents preserved in the Gāndhārī language that originate from Afghanistan and Pakistan. READ version 1.1 was completed in March 2016.
READ has been designed as a comprehensive multi‐user research workbench and publishing platform for ancient Sanskrit and Prakrit texts.
The design approach has been to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle is atomization of data to its smallest indivisible components and the linking and sequencing of these entities. This approach allows for attribution and annotation at every entity to record scholarly contribution at the finest level of granularity.
A great deal of work has been undertaken on the design and development of a comprehensive, extensible and configurable system ontology. The ontology provides standardized terms for both Physical and Textual domains; everything from object shapes and types to grammatical categories such as declension and conjugation values. These standard terms manifest as constraints within the system and ensure data consistency and quality.
READ is based on open source software and built to open standards. It provides an extensible entity model and a published API for integration with related systems. The technology stack includes PostgreSQL with backend development in PHP and UI development using JQuery. Fundamental to the design of READ is support for the import and export of TEI. The method adopted is XSLT transformation to EpiDoc specifications of an XML rendition of stored data. Import is the same process in reverse. Whatever format existing transcriptions were developed in these can be consumed, elaborated upon, analyzed, and then published as research output in TEI.
In summary, READ has been designed to functions as:
• a linked repository of images, transcriptions, translations, metadata, commentary and bibliographic records,
• a content management system encompassing multi-user editing, maintenance and version control,
• a collaboration platform with comprehensive access and visibility control to support draft development, workgroup collaboration and public presentation,
• a research workbench with access to a dictionary, corpus of texts, catalogs, glossaries, concordances and bibliography
• a publishing platform for individual transcription renditions or full scholarly editions, both print-ready and online, and
The kernel of an integrated research network interfacing with related dictionaries, repositories of parallel texts, GIS, data visualization, image rendering and palaeographic analysis systems.
The READ project commenced in 2013 with development support from a consortium of universities (Ludwig Maximillian University, Munich, the University of Washington, Seattle and the University of Lausanne), which, together with the University of Sydney, are involved in the study and publication of ancient Buddhist documents preserved in the Gāndhārī language that originate from Afghanistan and Pakistan. READ leverages 10 years of development on gandhari.org by Stefan Baums and Andrew Glass; the site that currently supports the Gāndhārī Dictionary, Bibliography and Catalog, as well as a comprehensive textual corpus. READ model and UI design is nearing completion and development is on track for delivery in late 2015.
READ has been designed as a comprehensive multi‐user research workbench and publishing platform for ancient Sanskrit and Prakrit texts: manuscripts, inscriptions, coins and other documents. READ is based on open source software and built to open standards. It provides an extensible entity model, TEI support and a published API for integration with related systems.
This presentation will focus on design aspects as encapsulated in the entity relationship model (ERM). An ERM is an abstract way of describing a relational database; most often represented as a flow chart accompanied by precise descriptions of each entity. This approach allows one to model the entities and their relationships and determine the most effective and flexible way of structuring the data to support authoring, storage, maintenance, analysis, reporting and publishing.
The design approach has been to build a comprehensive set of entities, mapped to real world objects, in order to seamlessly model both physical and textual domains. The underlying design principle is atomisation of data to its smallest indivisible components and the linking and sequencing of these entities.
As an illustration, in the physical realm, manuscripts or other inscribed ITEMS have PARTS, FRAGMENTS and SURFACES. IMAGES of these SURFACES are segmented to provide a fixed reference system, a BASELINE much like the grid laid out at an archaeological excavation. These SEGMENTS are then sequenced into SPANS across a SURFACE. SURFACES can then be aligned and the SPANS sequenced into complete LINES. The mapping between physical and textual is where SYLLABLES are identified with akṣara (the graphical unit of the kharoṣṭhī script these texts are rendered in) SEGMENTS. SYLLABLES (deconstructed into GRAPHEMES) are sequenced into TOKENS (words or compounds) which are ultimately sequenced up through textual divisions into full EDITIONS.
The philological process model adopted is one of defining each entity by applying classifying metadata and progressively sequencing these entities from the smallest upwards. This approach allows for attribution and annotation at every entity to record scholarly contribution at the finest level of granularity. Different editor's interpretations of akṣara SEGMENTS, SYLLABLE assignation and TOKEN grammatical deconstruction are all attributed and multiple versions of all entities exist in parallel to support the publishing of any number of alternative Editions.
In summary the design approach rests on a small number of basic principles:
• Firstly, by designing entities and their relationships to reflect real world objects in the domain one can flexibly map system functions to actual philological processes.
• Secondly by completely atomizing physical and textual objects one can flexibly sequence these components into higher level entities.
• Thirdly, the application of metadata and progressive sequencing of entities from the smallest component upwards through scale supports flexibility and granularity.
The technology stack includes PostgreSQL with backend development in PHP and UI development using JQuery; all mainstream open source development environments. A conventional software architecture has been adopted with:
• A data storage system built on relational database where entities are realized as tables with constraints and triggers to implement model logic and integrity.
• A storage abstraction layer implemented as server side libraries to expose entities and entity aggregates needed to support the web services.
• A variety of services including import, export, index, query and data management. Services are being implemented as using Ajax for complex interactive UI functions.
• A Javascript User interface using JQuery frameworks.
• A Javascript API to provide access to libraries and core services to allow for system extensions and integration.
A great deal of work has been undertaken on the design and development of a comprehensive system ontology. The ontology provides standardized terms for both Physical and Textual domains; everything from object shapes, mediums and types to grammatical categories such as declension and conjugation values. These standard terms manifest as constraints within the system and ensure data consistency and quality.
The System ontology has been designed to be extensible and configurable to allow READ to encompass alternative schema and new research objectives. Users can develop their own terms sets within the ontology to address their own research questions. For example, my research encompasses the development of metadata model for the analysis of formula structures in relic inscriptions, others wish to address syntactical structures and still others questions of metre.
A practical example of the flexibility in the ontology is the support for languages other than Gāndhārī. READ has been designed from the ground up to support all languages that have Sanskrit as their primordial. Branching in the system ontology allowing for alternative grammatical deconstructions enables READ to be easily configured for Sanskrit or Pali corpora, indeed any Prakrit language.
Fundamental to the design of READ is support for the import and export of TEI. The method adopted has been the development of services to export a complete XML rendition of stored data with XSLT transformation to EpiDoc TEI specifications. Import is the same process in reverse.
A highly sophisticated parser was developed to read the existing corpus of transcriptions from gandhari.org as text strings and shred these into READ database entities maintaining linkages. This parser can be finessed for other corpora that might currently only exist in unstructured formats like Word. Fundamental to READs design is support for import of existing datasets and export as XML and specifically TEI.
Indeed READ is positioned as a workbench for ancient documents, complementary to TEI based textual repositories such as SARIT and integrated with existing Sanskrit dictionaries. Whatever format existing transcriptions were developed in these can be consumed, elaborated upon, analyzed, and then published as research output in TEI or pdf. The data remains open source and can be exported as a full XML archive.
In summary, READ has been designed to functions as:
• a linked repository of images, transcriptions, translations, metadata, commentary and bibliographic records,
• a content management system encompassing multi-user editing, maintenance and version control,
• a collaboration platform with comprehensive access and visibility control to support draft development, workgroup collaboration and public presentation,
• a research workbench with access to a dictionary, corpus of texts, catalogs, glossaries, concordances and bibliography
• a publishing platform for individual transcription renditions or full scholarly editions, both print-ready and online, and
• The kernel of an integrated research network interfacing with related dictionaries, repositories of parallel texts, GIS, data visualization, image rendering and palaeographic analysis systems.
READ enables a very granular data structure and whilst the level of elaboration is dependent upon the research requirement, to derive most benefit, entails an initial investment in the application of metadata at each level of sequenced entities. The dividend is that this enables a range of automated analysis outputs which support palaeographic, phonological, grammatical, orthographical and morphological research in addition to the opportunities opened up for formulae and syntactical analysis.
The GRS is the next incarnation of the software platform that currently supports the Dictionary of Gāndhārī, Bibliography of Gāndhārī Studies and Catalog of Gāndhārī Texts by Stefan Baums and Andrew Glass, as well as the source‐text corpus assembled by them on gandhari.org. With development support from a consortium of four universities, the GRS project commenced in 2013 to redevelop the current system into a comprehensive multi‐user research workbench and publishing platform for ancient Sanskrit and Prakrit texts: manuscripts, inscriptions, coins and other documents:
• a linked repository of images, transcriptions, translations, metadata, commentary and bibliographic records,
• a content management system encompassing import, editing, maintenance, analysis and publishing,
• a collaboration platform with comprehensive access and visibility control to support draft development, workgroup collaboration and public presentation,
• a research platform for the production of catalogs, glossaries, concordances and grammatical analyses, and
• a flexible system for publishing individual transcription renditions or full scholarly editions, both print-ready and online.
The GRS is a database platform based on open source software and built to open standards. It provides an extensible entity model, TEI support and a published API for integration with related systems.
An entity relationship model is an abstract way of describing a relational database; most often represented as a flow chart accompanied by precise descriptions of each entity. This approach allows one to model the entities and their relationships and determine the most effective and flexible way of structuring the data to support authoring, storage, maintenance, analysis, reporting and publishing. The underlying design principle of the GRS is the atomisation of data to its smallest indivisible components and the linking and sequencing of these entities. The design approach has been to build a comprehensive set of entities which model real world objects. Manuscripts or inscribed items have parts, fragments and surfaces. Images of these surfaces can be segmented to provide a fixed reference system, a baseline much like the grids laid out at an archaeological excavation. Syllables can then be mapped to these image segments and sequenced into spans across a surface of a fragment of a manuscript. These fragments can then be aligned and the spans sequenced into complete lines.
The philological process model adopted is one of defining each entity by applying classifying metadata and progressively sequencing these entities from the smallest upwards. This approach allows for attribution and annotation of different interpretations of syllable, words, etymology and translation in order to record scholarly contribution at the finest level of granularity. Multiple versions of all entities may exist in parallel to support the publishing of alternative editions of a text.
The application of metadata to each entity in the system enables a range of automated analysis outputs which support palaeographic, phonological, grammatical, orthographical and morphological research in addition to the opportunities opened up for formulae and syntactical analysis.
A comprehensive database model has been designed through modelling the objects in the domain, mapping the philological process and atomizing the data down to the smallest indivisible components. The research platform under development will support authoring, storage, maintenance, analysis, reporting and publishing of a dictionary of Gāndhārī and a repository of Gandhāran inscriptions, manuscripts documents and coins. The presentation focused on the context and outline of the entire entity relationship model with a detailed presentation on areas of the model relevant to the alignment of multiple editions of a text.
The formulae observed: obeisance, donation, establishment, honor, benefit, identification and devotion provide a compelling insight into the ritual practice of the identification of the relics with the historical Buddha and their instantiation as the 'ultimate' body of the Buddha.
The current research project is centred on the development of methodologies for the analysis of these reliquary inscriptions and the characterization of the ritual practices associated with relic establishment in Gandhāra. The presentation will focus on the initial phase of the project, the development of a comprehensive metadata model and an exposition of some of the findings from an initial analysis of the formula structures.
Preliminary analysis has proven productive. In particular, modelling the themes of 'ritual practice' and 'identification and instantiation' has exposed a ritual strategy which shifts from relic provenance to relic transformation; from identification of the relics with the historical body of the Buddha to identification with the attributes and qualities of the dharma body of the Buddha.
This transformation, effected by liturgy, imbues the relics with the attainments and qualities of the Buddha, in what would seem to indicate their ritual and functional equivalence to the Buddha.
In particular, modelling of the themes of 'ritual practice' and 'identification and instantiation' exposes a narrative strategy of relic provenance, a literal and literary meme 'of the Buddha', which segues into a narrative of relic transformation. The ritual strategy exposed identifies the relics of the historical Buddha with the attributes and qualities of the dharma body of the Buddha. A transformative miracle effected by a liturgy of evocation, the ritual articulation of the qualities and attainments of the Buddha, pervades the relics with the attainments of the Buddha in what would seem to be indicative of a ritual and functional equivalence rather than an ontological sameness.
canon, the primary scriptures of Theravāda Buddhism. This is the story of a recent project to preserve and record the stones.