Trusted Facts: Triplifying Primary Research Data Enriched with Provenance Information
A crucial task in a researchers’ daily work is the analysis of primary research data to estimate the evolution of certain fields or technologies, e.g. tables in publications or tabular benchmark results. Due to a lack of comparability and reliability of published primary research data, this becomes more and more time-consuming leading to contradicting facts, as has been shown for ad-hoc retrieval . The CODE project  aims at contributing to a Linked Science Data Cloud by integrating unstructured research information with semantically represented research data. Through crowdsourcing techniques, data centric tasks like data extraction, integration and analysis in combination with sustainable data marketplace concepts will establish a sustainable, high-impact ecosystem.
KeywordsData Cube Code Project Provenance Information Semantic Enrichment Existent Concept
- 1.Armstrong, T.G., Moffat, A., Webber, W., Zobel, J.: Improvements that don’t add up: ad-hoc retrieval results since 1998. In: Proceedings of the Conference on Information and Knowledge Management, pp. 601–610 (2009)Google Scholar
- 2.Stegmaier, F., Seifert, C., Kern, R., Höfler, P., Bayerl, S., Granitzer, M., Kosch, H., Lindstaedt, S., Mutlu, B., Sabol, V., Schlegel, K., Zwicklbauer, S.: Unleashing semantics of research data. In: Proceedings of the 2nd Workshop on Big Data Benchmarking (2012)Google Scholar
- 3.Gollub, T., Stein, B., Burrows, S., Hoppe, D.: Tira: Configuring, executing, and disseminating information retrieval experiments. In: Proceedings of the 23rd International Workshop on Database and Expert Systems Applications, pp. 151–155 (2012)Google Scholar