Innovation fund for IT in research projects

The Research IT programme has a fund for small, innovative research projects by researchers of Utrecht University (UU). The goal of this innovation fund is to supply start-up capital for good innovative ideas in the field of IT and research. The goal of this innovation fund is to apply innovative IT to research. The selected proposal will allow a researcher to spend a modest sum in order to find out if the idea is viable. These pilots may entail risks; a chance of failure is considered acceptable.

The approved application(s) will be published on this page, as will the mandatory final report.

 

Criteria
  • The project must be based on an underlying scientific research question that can be answered more easily, quicker or more effectively with the help of an innovative IT application;
  • The idea must have potential for wider application (or adaptation for use) in other areas of research down the road;
  • It must be clear what final product is anticipated: tool, technique, report, knowledge, etc.;
  • Minimum of €10k, up to a maximum of €25k;
  • To qualify, the idea in question must not have funding readily available elsewhere, such as in connection with a strategic theme;
  • Interdisciplinary projects are preferred, while a connection (existing or sought) with the Applied Data Science focus area is desirable;
  • Applications will be submitted by a researcher employed by UU;
  • May be ‘risky’, a chance of failure is acceptable;
  • In carrying out the project, the Research IT programme will attempt to establish areas of connection with other activities within the programme.
Submitting an application

A new round of the innovation fund is expected at the end of 2019.

APPROVED APPLICATIONS 2018

Dr. ir. Ronald Poppe: VIABLE: VIdeo Analysis of Behavior: a Large-scale Experiment

Dr. Ioanna Lykourentzou: Collaborative crowdsourcing tools for sustaining intangible urban heritage

Prof. dr. Aoju Chen: Automatic Analysis of Speech Prosody (AASP)

Dr. Tanja Nijboer: Eye movement signatures of dysfunctions in visual attention during virtual reality simulations

Dr. Kim Cohen: Rhine-Meuse-Delta digital mapping: Going 1.0 to 3.0 by launching a MediaWiki communal catalogue

Prof. dr. Leonard Rutgers: A Time to Every Purpose under Heaven: Extracting Dates from Hebrew and Aramaic Texts

Dr. Marco Helbich: Deep learning from street view data: An alternative to traditional environmental exposure assessments?

Dr. Marjolijn Vermande: Adapting Qualtrics for peer report questionnaires

Approved applications 2017
Dirk Gerritsen, Arnout van de Rijt

IT infrastructure for a novel social influence experiment
Faculty of Law, Economics and Governance - Economics, Social Science

Rens van de Schoot Automatische Systematic Review
Faculty of Social Sciences - Methodics & Statistics

 
Joris van Eijnatten Historicized Place Name Disambiguation in Multilingual Repositories
Faculty of Humanities - History
 
Miroslav Zivkovic Adaptive text mining with mobile eye-tracking devices
Faculty of Science - Informatics
 
Peter Lugtig et al. App for recording sensor-data using smartphones
Faculty of Social Sciences - Methodics & Statistics
 
Erik Jan van Leeuwen, Arnout van de Rijt  Bestrijding van Nepnieuws in Sociale Netwerken
Faculty of Science & Faculty of Social Science - informatics and sociology
 

 

More information
Project Manager
University Corporate Offices - Information and Technology Services - Research and Data Management Services