Description
Leader of the group Information Access: Jacco van Ossenbruggen.
Our research group develops methods and techniques to better support users in accessing information that is heterogeneous, subjective and potentially inconsistent. We focus on the information’s context, using knowledge graphs to model differences in time and other relevant perspectives.
We work together with social scientists and humanities researchers to evaluate how technology can be used to best interpret complex data, by modelling and comparing different assumptions underlying the interpretation. We advocate the notion of transparency in all critical use of technology to improve trust assessments.
Please visit our publication or demo page for recent updates.
News
CWI research leads to better understanding of AI classification errors
The future of artificial intelligence (AI) looks bright, but AI is not infallible. In her PhD thesis, CWI researcher Emma Beauxis-Aussalet provides methods to make classification errors more transparent and understandable for end-users with limited expertise in AI.
Readers can increase retrievability of documents in the National Library collection
Crowdsourcing can help decrease the bias of the search engine of the ‘Koninklijke Bibliotheek’, the National Library of the Netherlands. CWI researchers will present that finding at the Joint Conference on Digital Libraries in Texas, which takes place on 4 June 2018.
Female members of European Parliament more likely to be featured on Wikipedia
Researchers from CWI have found that female members of the European Parliament are slightly more likely to be featured on multiple Wikipedia language editions than their male counterparts. However, the variations between language editions are large: while 10 editions over-represent women, 13 editions over-represent men.
ADS & Insight PhD position at CWI
Amsterdam Data Science, in which CWI participates as a partner, recently announced that 3 PhD projects will shortly commence, fully funded by Science Foundation Ireland (an award of around 0.5M€).
Members
Associated Members
Publications
-
Bucur, C.I, Kuhn, T, & Ceolin, D. (2019). Peer reviewing revisited: Assessing research with interlinked semantic comments. In Proceedings of the International Conference on Knowledge Capture (pp. 179–187). doi:10.1145/3360901.3364434
-
van Aggelen, A.E, Fokkens, A, Hollink, L, & van Ossenbruggen, J.R. (2019). A larger-scale evaluation resource of terms and their shift direction for diachronic lexical semantics. In Proceedings of the Nordic Conference on Computational Linguistics (pp. 44–54).
-
Angelopoulos, N, & Wielemaker, J. (2019). Advances in big data bio analytics. In Electronic Proceedings in Theoretical Computer Science, EPTCS (pp. 309–322). doi:10.4204/EPTCS.306.36
-
Bogaard, T, Hollink, L, Wielemaker, J, van Ossenbruggen, J.R, & Hardman, L. (2019). Metadata categorization for identifying search patterns in a digital library. Journal of Documentation. doi:10.1108/JD-06-2018-0087
-
Maddalena, E, Ceolin, D, & Mizzaro, S. (2019). Multidimensional news quality: A comparison of crowdsourcing and nichesourcing. In Proceedings of the CIKM 2018 Workshops co-located with 27th ACM International Conference on Information and Knowledge Management.
-
Dijkshoorn, C, Aroyo, L, van Ossenbruggen, J.R, & Schreiber, G. (2018). Modeling cultural heritage data for online publication. Applied Ontology, 13(4), 255–271. doi:10.3233/AO-180201
-
Ceolin, D, van Ossenbruggen, J.R, Aroyo, L, Sener, O, Sharma, R, Tkacz, L, & Noordegraaf, J. (2018). Assessing and visualising online information quality. In IEEE 14th International Conference on e-Science (e-Science) (pp. 356–357). doi:10.1109/eScience.2018.00096
-
Bilgin, A, Hollink, L, van Ossenbruggen, J.R, Tjong Kim Sang, E, Smeenk, K, Harbers, F, & Broersma, M. (2018). Utilizing a transparency-driven environment toward trusted automatic genre classification: A case study in journalism history. In IEEE 14th International Conference on eScience, e-Science 2018 (pp. 486–496). doi:10.1109/eScience.2018.00137
-
Maddalena, E, Ceolin, D, & Mizzaro, S. (2018). Multidimensional news quality: A comparison of crowdsourcing and nichesourcing. In Proceedings of the 6th International Workshop on News Recommendation and Analytics (INRA 2018).
-
Riguzzi, F, Wielemaker, J, & Zese, R. (2018). Probabilistic inference in SWI-Prolog. In CEUR Workshop Proceedings (pp. 15–27).
Software
Amalgame: Managing alignments in large vocabularies
Amalgame, short for AMsterdam ALignment GenerAtion MEtatool, is a Semantic Web tool for finding, evaluating and managing vocabulary alignments, i.e. relating corresponding concepts in different vocabularies.
Current projects with external funding
-
Automated Knowledge Graph Creation from Scientific Literature ()
Related partners
-
Elsevier