By Gio Wiederhold (auth.), Tansel Özyer, Keivan Kianmehr, Mehmet Tan, Jia Zeng (eds.)
The current paintings covers the newest advancements and discoveries on the topic of details reuse and integration in academia and business settings. the necessity for facing the massive volumes of information being produced and saved within the final many years and the varied structures built to accommodate those is more and more invaluable. no longer a majority of these advancements might have been accomplished with out the making an investment quite a lot of assets. over the years, new info resources evolve and knowledge integration remains to be a necessary and very important requirement. additionally, structures and items must be revised to evolve new applied sciences and wishes. rather than development those from scratch, researchers within the academia and have discovered some great benefits of reusing latest elements which were good demonstrated. whereas this pattern avoids reinventing the wheel, it comes on the fee of discovering the optimal set of current elements to be applied and the way they need to be built-in jointly and with the recent non-existing elements that are to be built. those nontrivial projects have ended in demanding learn difficulties within the academia and undefined. those matters are addressed during this ebook, that's meant to be a special source for researchers, builders and practitioners.
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Additional info for Information Reuse and Integration in Academia and Industry
Wiederhold use of rule engines allows representation of rules in a consistent formalism . These can then be interpreted by engines as CLIPS . Ontologies, if available, provide the meta-data for the description of data and information resources [19, 52]. If distinct resources have associated ontologies, the discovery of semantic matches and mismatches among distinct resources can be facilitated and partially automated . The technologies match those that are used for ontology-based integration .
Both may contain annotated sets. Further inputs are the referred ontology Ont, the annotation set of further process description elements POnt as well as already found combination triples in COM Ont and COM Part . The goal of the algorithm is to receive a refinement of these combinations as output COM Str . It traverses the given combinations in COM Ont [ COM Part found by Algorithms 1 and 2. First, it extracts the variable node pv by function getPV and the schema node s by function getSValue of the combination triple comi with 2 A Combination Framework for Exploiting the Symbiotic Aspects of .
IEEE Trans Softw Eng 14(9):1280–1292 48. Prabhu CSR (1992) Semantic database systems. Universities Press, Hyderabad 49. Risch T (1989) Monitoring database objects. In: Proceedings of the VLDB 15, Amsterdam. Morgan Kaufmann, Palo Alto 50. Rowe N (1983) An expert system for statistical estimates on databases. In: Proceedings of the AAAI, Washington, DC 51. Shannon CE, Weaver W (1948) The mathematical theory of computation. Reprinted by The University of Illinois Press (1962) 52. Staab S, Studer R (eds) (2004, 2009) Handbook on ontologies.
Information Reuse and Integration in Academia and Industry by Gio Wiederhold (auth.), Tansel Özyer, Keivan Kianmehr, Mehmet Tan, Jia Zeng (eds.)