Monday 15 September 2014

Relations for Reusing (R4R) in a Shared Context: An Exploration on Research Publications and Cultural Objects


Will the rich domain knowledge from research publications and the implicit cross-domain metadata of cultural objects be compliant with each other? A contextual framework is proposed as dynamic and relational in supporting three different contexts: Reusing, Publication and Curation, which are individually constructed but overlapped with major conceptual elements. A Relations for Reusing (R4R) ontology has been devised for modeling these overlapping conceptual components (Article, Data, Code, Provence, and License) for interlinking research outputs and cultural heritage data. In particular, packaging and citation relations are key for building up interpretations for dynamic contexts. Examples are provided for illustrating how the linking mechanism can be constructed and represented as a result to reveal the data linked in different contexts.


Responding to recent developments (Section 1) that have challenged research data, ar-chival and cultural heritage communities to come up with a contextual framework to support a dynamic and shared context environment, we have proposed a framework (Section 2) composed of three activity contexts that can be identified for a shared common understanding. In Section 3, the establishment of an ontology, Relations for Reusing (R4R) facilitates the representation of contextual links between resources in diverse contexts. Thus, a shared context between research and cultural heritage domains not only can be identified through three activity contexts for a common understanding, but rela-tions existing in different contexts can be established and represented through the R4R ontology. In Section 4, we used R4R to represent a use case from the Digital Archives Taiwan in different scenarios to show how linking data from these two domains can enhance the semantic relationships with each other, as well as increase the potential for reusing and remixing when both are contextually linked. The above discussions are the answers to the questions raised in Section 1, and we further discussed and presented a comparison of five existing relation ontologies that distinguishes the R4R from previous works in Section 5.

The advantage of designing a new conceptual model to describe relations in a shared context is to ensure that articles, datasets, software codes, provenance and license information can be treated as first-class contextual objects. At the same time, the module-like design of RRObject and RRPolicy can be practiced in isolation, and the unifying repre-sentation of their relations is semantically clear enough but not so structurally heavy-weighted that curators or researchers would find it difficult to apply. The contextual framework and R4R ontology can be applied to representing the interlinking relations of digital collections to a semantic web format, and help standardize this process. The au-thors of this work also plan in the future to explore more use cases to test the validity and effectiveness of the framework and the R4R ontology.

In sum, the daT(S010384) is a digital object with rich metadata descriptions that are curated in the Curation context. It is published as a cultural object Y, with unique iden-tification, and is cited as a science object Z, interpreted by the citation relation for addi-tional professional interpretations. At the same time, the citing research can benefit from the implicit information embedded in the institution’s cataloging vocabularies for more domain knowledge. Through the exploration of the Shared Context and R4R represen-tation, the daT(S010384) now is capable of moving from its traditional role and acting “as a citation of active knowledge”, as outlined in [22]. Creating knowledge out of interlinked data [23] is thus one step forward by packaging provenance and license for a policy-aware Reusing context. As a result, when data sharing does not need to remove the data's initial context but rather embed it in a shared context, the difficulty to interpret the reused data [24] may be expected to be reduced through the use of the contextual framework and the R4R ontology proposed in this study.



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