Creative Commons Attribution 4.0 International
No source, born digital.
TEI 2017 Conference Abstracts.
The workshop is intended to be a tutorial with an active conversation between the participants and the workshop leader. It will not include practical hands-on exercises.
Since the mid-1990s there has been an increase in the interest for the design and use of conceptual models (ontologies) in library science as well as in Digital Humanities. In the text-oriented Digital Humanities, however, conceptual models and ontologies have been considered to be closer to database development than to text research. This was the prevailing view in the TEI community until recently. The introduction of Linked Data 8 years ago (Berners-Lee 2009) has put more focus on what we may call
Reproducibility of results is a core concept in text-based research as in all research. The content in information systems and virtual reconstructions in the cultural heritage sector are to a large degree directly based on information deduced from text studies. In many cases the links from the information system back to the texts are not available, and such links may be difficult to re-establish. Even if it is possible to re-establish them, the process may be too expensive. These links are necessary to enable reproducibility of the deduction, since they document how the conclusions are based on the texts.
Linked Data offers a simple and easy way to publish data in an open and uniform interface enabling others to link scholarly data resources. Thus Linked Data should be ideal for building resources in the Digital Humanities (Ore 1998).
The programmatic slogan of the Semantic Web and Linked Data community is: Anyone can say anything about anything.
That is, anything can be linked. From a scholarly and scientific point of view this is not satisfactory. Information is generated through exclusion using meaningful distinctions according to a common conceptual model or formal ontology. Thus meaningful information integration in a scholarly field using the Linked Data mechanism requires a common conceptual model for the context in question.
How should structured information, based on a reading of a text, be linked to the encoded text itself? It is important to base such linking on data standards evolved in the fields of text encoding and conceptual modelling. Thus, the understanding of text encoding represented by the TEI guidelines and the understanding of conceptual models represented by initiatives like the CIDOC CRM and FRBRoo should be combined.
A conceptual model or ontology is not a specification for a technical implementation, nor is it a closed vocabulary or a thesaurus. It should be the result of a conceptualisation of a domain and a result of ontological commitments based on this analysis and is usually expressed as a hierarchy of concepts connected with properties or relationships. There are some important principles which should be observed. First of all, the model should follow the open-world assumption.
The workshop is divided into four main parts
The workshop is intended to be a tutorial with an active conversation between the participants and the workshop leader. It will not include practical hands-on exercises.