Abstract
The vision of the Social Semantic Desktop defines a user’s personal information environment as a source and end-point of the Semantic Web: Knowledge workers comprehensively express their information and data with respect to their own conceptualizations. Semantic Web languages and protocols are used to formalize these conceptualizations and for coordinating local and global information access.
A core challenge is to integrate existing legacy Desktop data into the Social Semantic Desktop. Semantic lifting is the process of capturing the semantics of various types of (semi-)structured data and/or non-semantic metadata and translating such data into Semantic Web conceptualizations.
From the way the vision of the Social Semantic Desktop is being pursued in the NEPOMUK project, we identified several requirements and research questions with respect to knowledge representation. In addition to the general question of the expressivity needed in such a scenario, two main challenges come into focus: i) How can we cope with the heterogeneity of knowledge models and ontologies, esp. multiple knowledge modules with potentially different interpretations? ii) How can we support the tailoring of ontologies towards different needs in various exploiting applications?
In this paper, we present semantic lifting as a means to create semantic metadata and the Nepomuk Representation Language (NRL) as a means to represent these metadata. NRL is an approach to these two aforementioned questions that is based on named graphs for the modularization aspect and a view concept for the tailoring of ontologies. This view concept turned out to be of additional value, as it also provides a mechanism to impose different semantics on the same syntactical structure.
We furthermore present some of the ontologies that have been developed with the help of NRL in the NEPOMUK project to build the semantic foundations for the Social Semantic Desktop.
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Sintek, M., Handschuh, S., Scerri, S., van Elst, L. (2009). Technologies for the Social Semantic Desktop. In: Tessaris, S., et al. Reasoning Web. Semantic Technologies for Information Systems. Reasoning Web 2009. Lecture Notes in Computer Science, vol 5689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03754-2_6
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