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.



Conclusion


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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Reference (DOIs are auto generated by pdfx )

  • 1. Zimmermann, Andreas, Andreas Lorenz, and Reinhard Oppermann. An operational definition of context. Modeling and Using Context (2007): 558-571.  [DOI]
  • 2. Krafft, Dean B., et al. VIVO: Enabling national networking of scientists. Proceedings of the Web Science Conference. Vol. 2010.  [possible DOI]  [alternative DOI]
  • 3. Keßler, Carsten, Mathieu d'Aquin, and Stefan Dietze. Linked data for science and education. Semantic Web 4.1 (2013): 1-2.  [possible DOI]
  • 4. Haslhofer, Bernhard, and Antoine Isaac. data. europeana. eu: The europeana linked open data pilot. International Conference on Dublin Core and Metadata Applications. 2011.  [DOI]
  • 5. Malmsten, Martin. Making a library catalogue part of the semantic web. Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications (2008): 146-152.  [possible DOI]  [alternative DOI]
  • 6. Ford, Kevin. LC Classification as linked data. Italian Journal of Library and Information Science, 4.1 (2013): 161.  [possible DOI]  [alternative DOI]
  • 7. Shotton, David. Semantic publishing: the coming revolution in scientific journal publishing. Learned Publishing 22.2 (2009): 85-94.  [DOI]
  • 8. Keivanloo, Iman, et al. Towards sharing source code facts using linked data. Proceedings of the 3rd International Workshop on Search-Driven Development: Users, Infrastructure, Tools, and Evaluation. ACM, 2011.  [DOI]
  • 9. Wendl, Michael C. H-index: however ranked, citations need context. Nature 449.7161 (2007): 403-403.  [DOI]
  • 10. Bechhofer, Sean, et al. Why linked data is not enough for scientists. Future Genera- tion Computer Systems 29.2 (2013): 599-611.  [DOI]
  • 11. Skinner, Julia. Metadata in Archival and Cultural Heritage Settings: A Review of the Literature. Journal of Library Metadata 14.1 (2014): 52-68.  [DOI]
  • 12. Courtright, Christina. Context in information behavior research. Annual Review of Information Science and Technology 41.1 (2007): 273-306.  [DOI]
  • 13. Peirce, Charles Sanders. “Elements of Logic”, Chapter 2: Division of Signs. In: C. Hartshorne and P. Weiss (eds.), Collected Papers of Charles Sanders Peirce (2) (Thoemmes Press, Bristol, 1998): 134–272  [DOI]
  • 14. Huang, Andrea Wei-Ching, and Tyng-Ruey Chuang. Social tagging, online commu- nication, and Peircean semiotics: a conceptual framework. Journal of Information Science 35.3 (2009): 340-357.  [possible DOI]
  • 15. Legg, Catherine. Peirce, meaning, and the Semantic Web. Semiotica 2013.193 (2013): 119-143.  [DOI]
  • 16. Beaudoin, Joan E. Context and its role in the digital preservation of cultural objects. D-Lib Magazine 18.11 (2012): 1.  [DOI]
  • 17. Seneviratne, Oshani, LalanaKagal, and Tim Berners-Lee. Policy-Aware Content Re- use on the Web. The Semantic Web - ISWC 2009 (2009): 553-568.  [DOI]
  • 18. Carata, Lucian, et al. A primer on provenance. Communications of the ACM 57.5 (2014): 52-60.  [DOI]
  • 19. Lagoze, Carl, et al. Fedora: an architecture for complex objects and their relationships. International Journal on Digital Libraries 6.2 (2006): 124-138.  [DOI]
  • 20. Yu, Chih-Hao, and Jane Hunter. Documenting and sharing comparative analyses of 3D digital museum artifacts through semantic web annotations. Journal on Compu- ting and Cultural Heritage (JOCCH) 6.4 (2013): 18:1-20.  [DOI]
  • 21. Gerber, Anna, and Jane Hunter. Authoring, editing and visualizing compound objects for literary scholarship. Journal of Digital Information 11.1 (2010).  [possible DOI]  [alternative DOI]
  • 22. Srinivasan, Ramesh, et al. Digital museums and diverse cultural knowledges: Mov- ing past the traditional catalog. The Information Society 25.4 (2009): 265-278.  [DOI]
  • 23. Auer, Sören, and Jens Lehmann. Creating knowledge out of interlinked data. Semantic Web 1.1 (2010): 97-104.  [possible DOI]  [alternative DOI]
  • 24. Borgman, Christine L. The conundrum of sharing research data. Journal of the American Society for Information Science and Technology 63.6 (2012): 1059-1078. [DOI]
  • 25. Associated data publication can be accessed at http://guava.iis.sinica.edu.tw/r4r/examples  [possible DOI]  [alternative DOI]