The WIS research group concentrates in its research on engineering and science of the Web. The research specifically considers the role of Web data in the engineering of Web-based information systems. The group's research is aimed at improving the understanding of people's actions, interests, motivations, and behaviors on the Web, and subsequently leveraging that knowledge to build Web applications that are semantic, personalized and adaptive.

This includes topics in harvesting, integrating, transforming, analyzing, and retrieving Web data, with focus on the special properties of Web data, e.g. linked data, semantic data, semi-structured data. A large portion of Web data is human-made, e.g. in social networks or Twitter streams, and this brings scientific challenges in how to effectively attribute meaning to Web data. The size of the Web brings challenges in how to efficiently store, index, and analyze data at Web scale. WIS researchers and students strive to advance the state-of-the-art in relevant disciplines like user modeling, Web science, information retrieval, Web engineering, Web data management, and crowdsourcing.

At WIS, we are enthusiastic about doing science on the Web and in particular the Social Web, and we love to investigate the power of Web data technologies - we envision a Web that adapts to the demands of the individual people. 

"From Web Data to Information"

Trending research activities: Learning Analytics, ImREALSocialGlassWUDE, Delft Data Science (DDS)RDFGearsTwitter Incident ManagementAMSGeniUSU-Sem and Twinder.

  • Example: Learning Analytics 
    • MOOCs (Massive Open Online Courses) represent a form of web information systems that is revolutionising the way education is brought to people. MOOCs offer great opportunities to change how people learn, by analysing student interactions with the courseware and adapting the courseware to the learners. A better understanding and adaptation of the process of learning is fundamental to improve learning, online as well as in traditional campus-based teaching. 
    • The WIS group uses its expertise in web user modeling for learning analytics at scale for the objective of providing at scale education that fits the learner. Research subjects include tracking learners across MOOCs, study dropout behaviour, and learner-based recommendation of related material. Example: Learning Analytics, ImREAL.
  • Example: Urban Analytics
    • Given that most of the world population lives in cities, to solve urban problems is to improve quality of life for a considerable amount of users. The challenge is to improve the understanding of urban environments by enriching and interpreting big urban data through social sensing. Social Data generated by users in online social networks recently attracted a lot of attention as a potential source of knowledge to better understand urban environments, citizens, and (natural) phenomenon. However, as of today, there is no general theory able to establish the effectiveness of social data for predictive or descriptive purposes: intuitively, solutions that might work for a given city might not be as valuable for another one.
    • The WIS group uses its expertise in social web data analytics to study to what extent social data can be used to represent or describe the targeted reality, possibly in combination with other data sources such as census data. Research subjects include resolution of data, bias of cultural or technological nature in data and conclusions drawn from the data, and crowdsourcing for creating and interpreting social data. Example: SocialGlass, AMS
  • Example: Explainable Advice-Giving systems
    • Artificial Advice Givers support people in making choices and decisions, they propose and evaluate options while involving their human users in the decision-making process. Examples include recommender systems, and (semi-)autonomous systems.
    • The WIS group uses its expertise in human-computer interaction and intelligent user interfaces to improve the transparency and decision support of artificial advice givers. Research subjects include: visualizing consumption blind-spots, recommending sequences (of diverse) recommendations, and strategies for supporting critical thinking in classrooms. Example: ENSURE, SuSPECT.
  • Example:  Analytics for Academic Document Repositories
    • Academic publications are a central repository of human-knowledge, and are at the core of scientific advancements both in academia itself, but also of industrial progress. However, tapping into this vast repository of knowledge is a daunting and challenging task, as the number of available publications is growing with tremendous speed. Without proper support, it is often hard or even impossible to find relevant publications related to a given problem in a timely fashion. However, the near exponential growth of content in the recent years together with the shift to digital resources invalidated many well-proven workflows, demanding new solutions suitable for the current age and time.
    • The WIS group uses its expertise in information extraction and query processing to discover meaningful and useful meta-data for annotating academic document repositories, and ┬Ěto develop user-centered query capabilities utilizing that meta-data for innovative new query paradigms, as for example visual exploration or facetted navigation. Examples: Semantic Digital Libraries, Semantic Open Courseware


  • Theme: Web Data & Semantics
    • On the Web and in web-based information systems data management, data integration and linking are crucial: for content integration and semantics-based enrichment purposes, for making sense of user information for analytical purposes, for connecting content information and user information for adaptation purposes, or for architectural purposes. In the research on Web Data and Semantics the challenge is to develop theory, methods and techniques for data management, data integration and semantic linking in web-based information systems. This research draws heavily from database and Semantic Web research and explores how database theory and tooling can be transformed for the challenges of Web-based system architecture, e.g. systems that exploit semantic technologies. The WIS group has specialized in data management and integration on new web data languages, e.g. for linked data, and on cloud and service-based architectures.
  • Theme: Web Analysis & User Modeling
    • To engineer contemporary information systems in a Web that is highly adaptive and personal, it is essential to 'understand' the usage and users of these systems. In the research on Web Analytics and User Modeling the challenge is to develop theories, methods and techniques to diagnose and understand how systems are used. This includes modeling users of a system based on what they do on the Web, inside or outside of the system, for the purpose of the subsequent design or configuration of the system.The fields of analytics and user modeling are facing brand new challenges in contemporary information systems, because of the nature and type of the data available for modeling, e.g. big data, semi-structured data, user-generated data. The WIS group has in user modeling specialized in analyzing and modeling on the Social Web.
  • Theme: Web Engineering & Adaptation
    • Engineering contemporary information systems in the Web includes facilities to make the access to information depend on the user and the user's context of usage. In the research on Web Engineering and Adaptation the challenge is to develop methods and techniques to include adaptation and contextualization in the engineering of web-based information systems.The purpose is to construct information systems that continue to meet the demands of their end-users. The field of Web engineering and in particular adaptation is driven by the implications of a Web that is larger, more open, and more social than in earlier generations of Web applications: the focus is on the realization of solutions that allow to incrementally embed and configure adaptation as part of existing applications, thus extending and enriching them. The WIS group has in adaptation engineering specialised in semantics-based and user model-driven adaptation.
  • Vision: Web Data
    • One characteristic property of Web data is that it transforms the way we need to design and build information systems. Data has always been the main ingredient in an information system to represent the world or the process that the system is serving, both inbound to detect what is going on in that world and outbound to support and run that world. In the traditional approach, the complexity was in the software to make all of this happen and data was designed to fit the software. The Web has brought an abundance of data to 'use' and it enables to make systems with a much better, much more encompassing, and much more accurate view of what is going on in the world the system is meant to serve. It implies a new complexity - this complexity is in the data and relates to the understanding of how the data can be used in the system. It implies that we need to understand the data and what software can make of the data in terms of useful knowledge. In other words, we need to fit the software to the data, for making systems that effectively use web data. As scientists, we are inspired to study data and technology for making sense of data, to make information system engineering make full use of web data.This reversing of the paradigm comes also with a much higher degree of user-centeredness of systems. Web data is often used to assess how system users, like students, customers, travellers, patients, etc., can be served better and more tailored. The abundance of Web data allows to unlock more knowledge that allows a higher degree of customisation and adaptation of systems to users. As scientists, we are therefore specially enthusiastic about studying how data and technology for making sense of data help us towards better user-adaptation. In a broad interpretation, this is all part of research into user modeling, and comes with a variety of data processing research challenges.

Selected Research Activities

Among the current or recent research activities and projects that the WIS group performs in this research are:

  • AMS - Amsterdam Institute for Advanced Metropolitan Solutions
  • ATSearch - Adaptive Faceted Search on Twitter
  • CrossUM - Cross-system User Modeling on the Social Semantic Web
  • Data Bridges - Smart (user) data services in digital cities
  • Delft Data Science - Data Science & Big Data research at TU Delft
  • ENSURE - ExplaiNing SeqUences in REcommendations
  • GeniUS - Generic user modeling on the Social Semantic Web
  • GRAPPLE - Adaptation in technology-enhanced learning
  • Hera - Semantics-based adaptation engineering
  • ImREAL - Augmenting user models with real-world information in training and learning
  • Net2 - Semantic-based methodologies for networked web and knowledge engineering
  • PoliMedia - Linked Open Politics (winner of LinkedUp Challenge)
  • RDF Gears - Data integration for the Semantic Web
  • SEEQR - Structural indexing and EfficiEnt Query processing on massive RDF data sets
  • SocialGlass - Your City Through the Social Data Lens
  • SuSPECT - Scaffolding Student PErspectives for Critical Thinking
  • TweetUM - Analyzing and modeling user behavior on Twitter for recommending trending news on the Social Web
  • Twitcident - Using relevant tweets during big incidents
  • Twinder - Finding interesting information in Social Web streams
  • U-Sem - Holistic User Modeling on the Social Semantic Web
  • WUDE - Web user demand elicitation in cultural heritage access

Research Community & Service

A selection of upcoming and recently organized conferences or workshops that WIS group members helped to organise and chair:

  • CitRec 2017 - Recsys Workshop on Citizens' Recsys
  • IntRS 2017 - Recsys Workshop on Interfaces and Human Decision Making for Recommender Systems
  • MSR Challenge 2017 - 14th Conference on Mining Software Repositories: mining challenge
  • BeyondMR 2015 - EDBT Workshop on Algorithms and Systems for MapReduce and Beyond, 27 March, 2015
  • EDBT Summer School 2015 - The EDBT Summer School on Graph Data Management 2015, Aug 31 - Sept 4, 2015
  • ACM HT 2015 - 26th ACM Conference on Hypertext and Social Media, Cyprus, September 1-4, 2015.
  • ICWE 2015 - 15th International Conference on Web Engineering, Rotterdam, the Netherlands, June 22-26, 2015.
  • UMAP 2014 - 22nd Conference on User Modeling, Adaptation and Personalization, Aalborg, Denmark, July 7-11, 2014.
  • ICWE 2014 - 14th International Conference on Web Engineering, Toulouse, France, July 1-4, 2014.
  • WebSci 2014 - ACM Web Science 2014 Conference, Bloomington, USA, June 23-26, 2014.
  • UMAP 2013 - 21st Conference on User Modeling, Adaptation and Personalization, Rome, Italy, June 10-14, 2013.
  • Web Engineering at WWW2013 - 22nd International World Wide Web Conference, Rio de Janeiro, Brazil, 13-17 May 2013.

The following is a non-exhaustive list of research events that WIS group members are or have been involved in as chair, organizer or committee member:

  • IUI2018
  • ESWC2017, EvalUMAP2017, Hypertext2017, ICWE2017, ICSME2017, ISWC2017, L@S2017, MSM2017, MSR2017, Recsys2017, UMAP2017
  • AIMSA2016, BLINKS2016, EvalUMAP2016, ESWC2016, Hypertext2016, ICWE2016, ISWC2016, MSM2016, UMAP2016, USEWOD2016, WebSci2016, WWW2016
  • CSSWS2015, DeCAT2015, ESWC2015, HT2015, I3E2015, ICWE2015, ISWC2015, MSM2015, PATCH2015, RDSM2015, SPS2015, UMAP2015, USEWOD2015, WebSci2015, WWW2015, GRADES 2015
  • CrowdSens2014, CSSWS2014, ICWE2014, IESD2014, ISWC2014, SP2014, UMAP2014, USEWOD2014, WebSci2014, WISM2014
  • ComposableWeb2013, CulTEL2013, EDBT2013, HT2013, i-KNOW2013, ICWE2013, IESD2013, ISWC2013, MDWE2013, MSM2013, RAMSS2013, SALAD2013, SMERST2013, UMAP2013, WISM2013, WWW2013
  • AAAI2012, ECIR2012, ESWC2012, HT2012, ICWE2012, I-Semantics2012, LAPIS2012, MultiA-Pro2012, RAMSS2012, UMAP2012, WebSci12, WISM2012, WWW2012
  • AUM2011, BEWEB 2011, CHI 2011, CIKM 2011, ComposableWeb2011, DAH2011, EDBT 2011, ESWC 2011, EUROITV2011, FOMI2011, HT2011, ICWE 2011, IJCAI2011, I-Semantics 2011, ISWC 2011, LISC2011, MDWE2011, MMM2011, MODIQUITOUS-2011, MSW2011, SASWeb2011, SIGIR 2011, SocialObjects2012, S3T 2012, UMAP2011, USEWOD2011, UWEB2011, VISSW 2011, WebSci11, WeRE 2011, WIN2011
  • AIMSA 2010, ComposableWeb'10, Coopis 2010, EDBT 2010, EIS 2010, EKAW2010, ESWC2010, HT2010, ICDKE 2010, ICWE2010, KMIS 2010, LUPAS2010, MDWE 2010, PODS 2010, QWE'10, RecsysTEL-2010, SASweb 2010, SLE 2010, SOFSEM2010, UDISW2010, UMAP2010, WABBWUAS2010, WANDS 2010, WebSci10, WECU2010, WISH2010, WSW2010
  • ABIS2009, CIKM 2009, ComposableWeb2009, DAH2009, EDBT 2009, ESWC 2009, HT 2009, ICOODB 2009, ICSC 2009, ICWE 2009, KMIS 2009, Mashups09, MDWE2009, MMM2009, SWIM 09, UMAP09, WISE 2009, WISM2009, WWW2009
  • AH2008, CIKM2008, EDBT 2008, HT 2008, ICWE 2008, MDWE2008, MMM2008, PATCH 2008, SOFSEM 08, WISE 2008, WISM2008, WWW2008

Further, WIS group members are board member of the following journals:


And they have been involved in reviewing and special issue editing for these and many other relevant journals, for example JoDI, JWS, SWJ, DKE, IEEE IntSys, IJHCS, IJSWIS.