Lora Aroyo is a Full Professor and head of the User-Centric Data Science Group (UCDS), Department of Computer ScienceDepartment of Computer Science, VU University Amsterdam. She is involved in several research projects focussed on understanding ambiguity and teaching machines to deal with ambiguity by applying techniques from crowdsourcing and human computation, data science, data quality assessment, and especially hybrid human-AI systems for text and video understanding. She has led major research projects in applying Semantic Web technologies for semantic search, recommendation systems, event-driven access to online multimedia collections, and through these has become a recognized leader in digital humanities, cultural heritage, and interactive TV.

Current projects include:

  • ReTV: Re-purposing and re-using digital content across Smart TVs, Web and mobile applications, social media and other emerging platforms
  • Capturing Bias: models for bias- and diversity-aware accuracy measures for reliable and explainable big data analysis of media collections
  • CrowdTruth: human-assisted computing, specifically targeting workflows for the creation of ground truth data
  • DIVE: Event-centric Exploration of Linked Heritage

Past projects include:

  • Accurator: Annotating Fashion with Nichesourcing
  • SealincMedia:  Socially-enriched Access to Linked Cultural Media
  • CLARIAH: Common Lab Research Infrastructure for the Arts and Humanities
  • ControCurator: discover and understand controversial topics and events
  • VISTA-TV: Combining LOD and behavioral information for TV analyses
  • PrestoPrime: WAISDA? Crowdsourcing Game for Video Annotation
  • NoTube: integration of Web and TV data with the help of semantics
  • CHIP: Cultural Heritage Information Personalization

I am working with both IBM Research in NY and IBM CAS in Amsterdam on crowdsourcing ground truth data for the adaptation of the Watson system in medical domain [slides]:

  • Dr. Watson: Gamification of Ground Truth Collection for Medical Texts
  • Crowd-Watson: Framework for Crowdsourcing Ground Truth Data
  • Crowd Truth: Metrics to Evaluate Crowdsourced Ground Truth Data

I am chief scientist at Tagasauris Inc., a New York-based startup that works on machine learning and human-assisted computing strategies to enrich video with precise, meaningful information about its content, and thus improve video search and discovery.

If you are looking for a bachelor, master or PhD project in the context of the projects above send Lora Aroyo an email or request an appointment. Check out also the current student projects.

Check also the experimental research facilities in our VU INTERTAIN Lab.

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Stitch by Stitch: Annotating Fashion at the Rijksmuseum

Fashion can be found everywhere in museums. Fashion heritage collected over centuries: costumes, accessories, paintings, prints and photographs. But while some clothes and accessories are easily found and identified, others are obscure and require a trained eye to describe. What are we looking at? What kind of sleeve is this? Which materials and techniques have been used? More specific descriptions of the images facilitate better use of digital collections and enable users to wander through them in detail.

Modemuze is an online platform and network of 11 Dutch museums, including Rijksmuseum, with a fashion and costume collection: Amsterdam Museum, Centraal Museum Utrecht, Fries Museum Leeuwarden, Gemeentemuseum Den Haag, Museum Rotterdam, Paleis Het Loo, Rijksmuseum, Tassenmuseum Hendrikje, TextielMuseum, Theatercollectie Bijzondere Collecties UvA, Tropenmuseum, Afrika Museum, Museum Volkenkunde.

Annotating the collections

Researchers from VU University Amsterdam, Delft University of Technology and the Centre for Mathematics and Informatics and the Rijksmuseum (in the context of the COMMIT SealincMedia project) have developed Accurator: an online tool to improve the process of annotation of digital collection objects, e.g. being able to find relevant objects to annotate, annotate specific parts of an object, etc. Following ‘Birdwatching in the Rijksmuseum’, this time the Accurator tool will be used to describe fashion related objects from the Modemuze and Rijksmuseum collections.

Participants in the fashion annotation event are also invited to record their findings in the Wikipedia Encyclopedia, Wikimedia Commons and in Wikidata, Wikipedia’s open database. Wikipedia volunteers, as well as staff from the Rijksmuseum and Modemuze, will be present for support throughout the day.

Participation in the event is free, but registration is required. To register, please send an email to accurator@rijksmuseum.nl with your name and your interest in fashion. (We will take your subject preferences into account when setting up the Accurator tool.) If you have any questions regarding the event, please feel free to email them to this address.

Additional information

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Exploration is the New Search @ SXSW2017

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Slides from our TEDx Navesink 2015 talk

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The CrowdTruth Journey @VU Faculty Colloquium

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A twitter overview of the IUI2015

http://eventifier.com/event/iui2015/popular?full_embed=true

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Crowd Truth, public release v.1

Last week, 13-Jun-2014, we published the first public release of the Crowd Truth framework. The CrowdTruth description document will give you an overall view of the framework components. The CrowdTruth Guidelines document will help you logging in and using the system. On github you can find the CrowdTruth Code and future updates.

Please, be aware that this is still work in progress, and not all things work perfectly – so don’t give up right away and send us email with feedback, so that we can repair the bugs. If you have any problems using it, please contact us Lora Aroyo and Chris Welty and we will be happy to help you through the system.

 

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Crowd-Watson @NLeSC eHumanities Kick-off

Today at the NLeSc, during the “De Geest Uit De Fles” event six new projects kick off their research in the area of eHumanities. As part of this, the Crowd-Watson project team will collaborate with NleSC researchers in the coming 12 months for the development of the next version of the Dr. Watson, a medical detective nichesourcing game. Here you can find my slides on “Crowds & Niches Teaching Machines to Diagnose”:

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