Trusted facts: Triplifying primary research data enriched with provenance information

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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 [1]. The CODE project [2] 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. © Springer-Verlag 2013.




Schlegel, K., Bayerl, S., Zwicklbauer, S., Stegmaier, F., Seifert, C., Granitzer, M., & Kosch, H. (2013). Trusted facts: Triplifying primary research data enriched with provenance information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7955 LNCS, pp. 268–270).

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