Description
Leader of the group Human-Centered Data Analytics: Laura Hollink.
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.
Vacancies
No vacancies currently.
News
Podcast: Hoe kan AI controversiële termen in erfgoedcollecties opsporen?
CWI-onderzoeker Laura Hollink sprak in de podcast Snoek op Zolder over het Cultural AI Lab. Hoe kunnen waarden als diversiteit, inclusiviteit en respect voor culturele verschillen worden vertaald in AI-toepassingen?
Podcast: How can AI detect controversial terms?
Laura Hollink (CWI) talked about the Cultural AI Lab in the podcast 'Snoek op Zolder'. How can values like diversity and inclusiveness be translated into AI applications?
AI, Media & Democracy Lab receives NL AIC Label
The AI, Media & Democracy Lab is one of the first six labs to receive the NL AIC Label. At the Lab researchers will investigate various aspects of the use of artificial intelligence (AI) in the media.
New fifty pound British banknote honours computer pioneer Alan Turing
On 23 June the Bank of England releases a new banknote featuring Alan Turing. CWI researchers Lynda Hardman and Jurgen Vinju comment on the meaning of Turing’s work for present day computer science and society.
Members
Associated Members
Publications
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Soprano, M, Roitero, K, La Barbera, D, Ceolin, D, Spina, D, Mizzaro, S, & Demartini, G. (2021). The many dimensions of truthfulness: Crowdsourcing misinformation assessments on a multidimensional scale. Information Processing and Management, 58(6). doi:10.1016/j.ipm.2021.102710
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Ceolin, D, Doneda, F, & Primiero, G. (2021). Computable trustworthiness ranking of medical experts in Italy during the SARS-CoV-19 pandemic. In Proceedings of the Conference on Information Technology for Social Good (pp. 271–276). doi:10.1145/3462203.3475907
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Bogaard, T, Bilgin, A, Wielemaker, J, Hollink, L, Ribbens, K, & van Ossenbruggen, J.R. (2021). Comparing methods for finding search sessions on a specified topic: A double case study. In Digital Libraries for Open Knowledge (pp. 189–201). doi:10.1007/978-3-030-86324-1_23
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Ceolin, D, Primiero, G, Wielemaker, J, & Soprano, M. (2021). Assessing the quality of online reviews using formal argumentation theory. In International Conference on Web Engineering (pp. 71–87). doi:10.1007/978-3-030-74296-6_6
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van Aggelen, A.E, & Hollink, L. (2020). The Portrait of a Lady: Close and distant reading of media gender bias.
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Raad, J, Beek, W, van Harmelen, F.A.H, Wielemaker, J, Pernelle, N, & Saïs, F. (2020). Constructing and cleaning identity graphs in the LOD Cloud. Data Intelligence, 2(3), 323–352. doi:10.1162/dint_a_00057
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Bucur, C.I, Kuhn, T, & Ceolin, D. (2020). A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishing. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence. doi:10.1007/978-3-030-61244-3_7
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Ceolin, D, & Primiero, G. (Giuseppe). (2019). A granular approach to source trustworthiness for negative trust assessment. In Proceedings of the IFIP International Conference on Trust Management (pp. 108–121). doi:10.1007/978-3-030-33716-2_9
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Ceolin, D, & Primiero, G. (2019). A granular approach to negative source trustworthiness. In Proceedings of the IFIP International Conference on Trust Management.
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Bogaard, T, Hollink, L, Wielemaker, J, Hardman, L, & van Ossenbruggen, J.R. (2019). Searching for old news: User interests and behavior within a national collection. In CHIIR '19 Proceedings of the 2019 Conference on Human Information Interaction and Retrieval (pp. 113–121). doi:10.1145/3295750.3298925
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
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Culturally aware AI (AI:CULT)
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The eye of the beholder: Transparent pipelines for assessing online information quality (None)
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Responsible Recommenders in the Public Library (PPS Koninklijke Bibliotheek)
Related partners
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Koninklijke Bibliotheek
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KNAW - Meertens Instituut