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Sprekers bij de 11de VOGIN-IP-lezing 16 maart 2023 |
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Sprekers |
![]() Joyce van Aalten is zelfstandig adviseur op het gebied van vindbaarheid van informatie. Hierbij heeft ze zich gespecialiseerd in het opzetten en toepassen van trefwoordenlijsten, taxonomieën, thesauri en knowledge graphs. Daarnaast is ze docent bij GO Opleidingen. Joyce is mede-auteur van het leerboek “Maak het vindbaar“ en heeft een hoofdstuk over taxonomietooling geschreven voor het boek “Taxonomies – Practical Approaches to Developing and Managing Vocabularies for Digital Information”. Joyce spreekt regelmatig op congressen, waaronder de Taxonomy Boot Camp in Londen. | web | blog | twitter | slides | li | Lezing: “Vijf vindbaarheidsproblemen waar een taxonomie de schuld van krijgt (maar niks aan kan doen)” |
![]() Elisabeth Bik, PhD is a Dutch-American microbiologist who has worked for 15 years at Stanford University and 2 years in industry. Since 2019, she is a science integrity volunteer and consultant who scans the biomedical literature for images or other data of concern and has reported over 6,000 scientific papers. Her work has resulted in over 900 retracted and another 900 corrected papers. For her work on exposing threats to research integrity, she received the 2021 John Maddox Prize. | blog | blog | wiki | twitter | mastodon | li | scholar | orcid | |
![]() Productmanager en designer bij de Universiteitsbibliotheek Gent. Opgeleid als designer, afgeleid door open kennis. Miet bouwt aan producten en diensten die kennis bijbrengen aan onze maatschappij. De rode draad in haar carrière is sinds 2012 (open) data omvormen tot informatie die mensen vooruithelpt – in startups, overheden en nu in de Boekentoren in Gent. Om aangename, gepaste ervaringen te bouwen, betrekt ze de mensen waarvoor we bouwt dicht in het proces. Co-creatie met ontwikkeling en business staan hier centraal. | twitter | li | slides | |
![]() Alastair Dunning is Head of Research Services at the library of Delft University of Technology. His professional concerns include fighting the hydra of closed formats, slaying the dragon of vendor lock-in and locating the elixir of openness. Previously, he worked for Europeana (the cultural heritage aggregator) and Jisc, the UK organisation enabling digital transformation in higher and further education. | web | blog | twitter | li | scholar | slides | figshare | flickr | orcid |
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![]() Odin Essers is de hoofdconservator van de Bijzondere Collecties van de Universiteit Maastricht en de drijvende kracht achter verschillende Wikimedia-gerelateerde activiteiten en projecten. Hij schreef mee aan het artikel Where history meets modern: an overview of academic primary source research-based learning programs aggregating special collections and Wikimedia, dat in 2021 verscheen in de open access publicatie Wikipedia and Academic Libraries: A Global Project. Opgeleid als docent Nederlands en als cultuurwetenschapper gespecialiseerd in mediacultuur, werkte Odin voorheen als eLearning-specialist voor de afdeling Onderwijs- en Onderzoeksondersteuning van de Universiteitsbibliotheek Maastricht en gaf hij training, support en advies aan studenten, docenten en onderzoekers. | web | twitter | boek | li | Lezing: “Oude boeken, nieuwe vaardigheden en Wikipedia” |
![]() Katariina Kari is IKEA’s lead ontologist and an active semantic web practitioner for the past 5 years. Before IKEA she was data engineer at Zalando, responsible for its fashion knowledge graph. Earlier, she was doing the digital transformation for classical music. Katariina holds a Master in Science (Engineering) degree, specialising in the semantic web, and a Master in Music (Arts Management) degree, specialising in guiding the art business to the digital age. | twitter | li | github | medium |
Lezing: “The three layers of a knowledge graph and what it means for authoring, storage, governance and data quality of the knowledge graph” |
![]() Prof. mr. dr. Reijer Passchier is als hoogleraar digitalisering en de democratische rechtsstaat verbonden aan de Open Universiteit en als universitair docent staats- en bestuursrecht aan de Universiteit Leiden. In 2021 publiceerde hij het boek ‘Artificiële intelligentie en de rechtsstaat’ bij Boom juridisch. Reijer trad op bij diverse media, gaf college in de nationale AI-cursus ethiek en adviseerde onder andere de Eerste Kamer. Op https://research.ou.nl/en/persons/reijer-passchier is meer informatie te vinden over o.a. publicaties en lezingen. | web | web | twitter | li | boek | Lezing: “Overleeft de rechtsstaat Big Tech?” |
![]() Nava Tintarev is a Full Professor of Explainable Artificial Intelligence at the University of Maastricht, and a guest professor at TU Delft. She leads or contributes to several projects in the field of human-computer interaction in artificial advice-giving systems, such as recommender systems; specifically developing the state-of-the-art for automatically generated explanations (transparency) and explanation interfaces (recourse and control). She is currently participating in a Marie-Curie Training Network on Natural Language for Explainable AI and is representing Maastricht university as Co-Investigator in the ROBUST consortium, pre-selected for a national (NWO) grant with a total budget of 95M (25M from NWO) to carry out long term (10-years) research into trustworthy artificial intelligence. She regularly shapes international scientific research programs (e.g., on steering committees of journals, or as program chair of conferences), and actively organizes and contributes to high-level strategic workshops relating to responsible data science, both in the Netherlands and internationally. She has published over 80 peer-reviewed papers in top human-computer interaction and artificial intelligence journals and conferences such as UMUAI, TiiS, ECAI, IUI, SIGIR, Recsys, and UMAP. Recently, these publications also received best paper awards at the Hypertext, HCOMP, and CHIIR conferences. | web | scholar | li | orcid | Lezing: “Why one-size-fits all does not work in Explainable Artificial Intelligence!” A lot of people recognize the importance of explainable AI. This is also the case for personalized online content which influences decision-making at individual, business, and societal levels. Filtering and ranking algorithms such as those used in recommender systems support these decisions. However, we often lose sight of the purpose of these explanations and whether understanding is an end in itself. This talk addresses why we may want to develop recommender systems that can explain themselves and how we may assess that we are successful in this endeavor. This talk will describe some of the state-of-the-art explanations in several domains (music, tourism, search results) that help link the mental models of systems and people. However, it is not enough to generate rich and complex explanations; more is required to support effective decision-making. This entails decisions around which information to select to show to people and how to present that information, often depending on the target users and contextual factors. [Lees ook dit interview met de spreker in de digitale IP] |