Modeling the digital scholarly edition beyond TEI, pt.2
Report of the workshop “TEI and neighboring standards,” with presentations from Stefanie Gehrke, Øyvind Eide and Peter Boot at the first DiXiT convention, 15th September 2015, Huygens ING.
By Merisa Martinez and Frederike Neuber.
While the first part of this blog post was dedicated to Stefanie Gehrke’s presentation on Open Annotation, Shared Canvas, and IIIF, in this second part we are going to review Øyvind Eide’s contribution on ontologies and in particular the CIDOC CRM, as well as Peter Boot’s presentation on metadata standards. As in the first post, we will only touch on the detailed architecture and functions of the models, and instead outline their potential for integration in digital scholarly editions.
Data about data or rather data itself
Before turning to the ontology section of the workshop, Peter Boot provided a helpful overview of different metadata formats such as METS, MODS, MIX and Dublin Core. The scope of all these metadata standards is the record of structured information used to aid identification, description, management and location of ressources, traditionally in libraries, archives and museums.
METS, MODS and digital scholarly editions
Particularly important in the context of digital libraries are the Metadata Encoding and Transmission Standard (METS) and the Metadata Object Description Schema (MODS). METS is an open, relatively simple and extensible metadata standard for encoding descriptive, administrative, and structural metadata regarding objects within a digital library. It is expressed in XML. A key function of the METS standard is to structure or “package” other metadata or data for exchange or delivery. METS can embed or link to other XML-based metadata (e.g. MODS, MIX, or TEI). Sometimes used as extension to METS, MODS is used to encode information about library resources (particularly books). It was designed as a compromise between the complexity of the MARC format used by libraries and the extreme simplicity of Dublin Core metadata. It is also expressed as XML.
In the context of a digital scholarly edition, those standards can become important when a number of digital files need to be described and linked together, enabling the representation of very complex digital resources (e.g. a whole digitized book, with bibliographic data, images and transcribed text) or even when we aim to integrate the data and resources of our digital scholarly editions into the framework of a digital library or collection.
Whitman Archive: http://www.whitmanarchive.org
Mark Twain Project: http://www.marktwainproject.org
Jane Austen’s Fiction Manuscripts Digital Edition: http://www.janeausten.ac.uk/
Slides: Metadata standards (Boot)
Modeling the world – at least a corner of it
In Information Science, ontologies are used to describe formal representations of a set of concepts within a domain and the relationships between those concepts. Studer et. al define an ontology as follows:
An ontology is a formal, explicit specification of a shared conceptualization. Conceptualization refers to an abstract model of some phenomenon in the world by having identified the relevant concepts of that phenomenon. Explicit means that the type of concepts used, and the constraints on their use are explicitly defined. Formal refers to the fact that the ontology should be machine-readable. Shared reflects that notion that an ontology captures consensual knowledge that is, it is not private of some individual, but accepted by a group.
Studer, R. Benjamins, V.R. and Fensel, D., 1998. Knowledge engineering: principles and methods. Data Knowledge Engineering, Elsevier Ltd, Volume 25, Issues 1-2, pp.161-197.
There is no correct way of modelling a domain, because in the end everyone has a different view of the world or of a certain corner of it. Nevertheless, ontologies can support shared conceptualizations of a domain and therefore facilitate collaboration and data exchanges within them.
One particular ontology which we were introduced to by Øyvind Eide is the CIDOC Conceptual Reference Model (CRM), an extensible ontology for the documentation of cultural heritage information and, since 2006, the international standard (ISO 21127) for the controlled exchange of information in the GLAM sector (galleries, libraries, archives, and museums). The goal of CIDOC CRM is to provide definitions and a formal structure for describing the implicit and explicit concepts and relationships used in cultural heritage documentation and to promote a shared understanding of them. To quote the CIDOC website:
In this way, it can provide the ‘semantic glue’ needed to mediate between different sources of cultural heritage information, such as that published by museums, libraries and archives.
Ontologies and perspectives for digital scholarly editions
Ontologies are still rarely integrated into digital scholarly editions, even if they could be useful for a lot of editorial scopes. Imagine
- many paleographers each modeling their domain (writing) in their own way. Sharing a common understanding of the domain using the same concepts and names among researchers would facilitate data interchange and collaboration.
- editing projects with similar or even the same research scopes, all starting from scratch building their data models. Ontologies enable the sharing and reuse of knowledge.
- an edition, marked up in TEI, which represents information as it appears on the document, failing to include references to i.e. persons. Sometimes there may be variant spellings for the same person, or same spellings of a given name which refers to more than one person, sometimes the reference will be implicit, and so forth. This information need to be modeled in a way that the computer understands who is meant and where it refers to.
- if a user of an edition is searching for a place but doesn’t know the exact name of that place. A highly structured and enriched ontology could enable a facetted search approach which limits the number of possible results (‘all cities with more than 350.000 inhabitants in Bavaria’).
- an editor who knows a lot about his material but has difficulties ordering this knowledge and revealing relations of concepts in it. Ontologies can also serve as models of knowledge, enhancing our understanding of the correlations within a certain domain.
Henry III Fine Rolls project: http://www.frh3.org.uk/home.html
Sharing Ancient Wisdoms: http://www.ancientwisdoms.ac.uk/
Slides: Ontologies and CIDOC CRM (Eide)
The workshop on TEI and neighboring standards was a helpful introduction to the presented topics. In the subsequent discussion it became evident that most of the participants didn’t have any previous experience with the use of the data models and standards and were not aware of the possibilities to model information beyond the TEI. However, a big problem in this context is the lack of workshops and schools for scholarly editors on i.e. on Semantic Web technologies and metadata standards. While the TEI is a very well organized and outreaching network in which the teaching of the younger generation of editors plays an important part, the communities behind the presented models are either directed to another audience (e.g. GLAM sector) or they are still quite young and in a growing-process and therefore not yet at a point to disseminate their knowledge. For this reason, the participants expressed the need for a more extensive, hands-on workshop which DiXiT (in collaboration with the Huygens Institute) plans to arrange in the near future.
* * *
Last but not least, we want to thank Peter Boot and the Huygens Institute for the organization of this workshop.