Opendata, web and dolomites


Knowledge Discovery in Data as Collaboration of Human and Software Actors

Total Cost €


EC-Contrib. €






Project "KDD-CHASER" data sheet

The following table provides information about the project.


Organization address
address: Glasnevin
city: DUBLIN
postcode: 9

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Ireland [IE]
 Total cost 175˙866 €
 EC max contribution 175˙866 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-02-01   to  2020-01-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DUBLIN CITY UNIVERSITY IE (DUBLIN) coordinator 175˙866.00


 Project objective

The KDD-CHASER project aims to develop a process model and software platform for collaborative knowledge discovery in data (KDD). Traditionally, KDD has been an expert-driven process, but more recently, special types of KDD processes have begun to emerge that involve non-expert individuals in various roles. With sufficiently intelligent software tools, it is even possible for such individuals to take charge of the process and use KDD to extract useful knowledge from their own personal data, but this possibility is not adequately covered by the established process model of KDD. The project addresses this problem by exploring the requirements of incorporating autonomous software and non-expert humans as actors in the KDD process and distilling these into a new process model, consisting of a data model and a workflow model, that satisfies the requirements.

The data model aims to provide a representation of the fundamental concepts of the KDD process, most importantly knowledge itself. The model forms an essential part of the foundation of new, more autonomous KDD software tools that are capable of carrying out tasks that currently require a human expert. The workflow model represents the actors of the KDD process - experts, non-experts and software - and the interactions through which they collaborate in different incarnations of the process. Once the models have been validated against their requirements, they will in turn be used to define requirements for a collaborative KDD software platform that can be used by diverse actors to establish teams and design solutions to KDD problems. Finally, the software platform will be implemented and validated by executing a test scenario involving knowledge discovery from personal lifelogs.


year authors and title journal last update
List of publications.
2018 Tuovinen, Lauri Smeaton, Alan F.
Ontology-based negotiation and enforcement of privacy constraints in collaborative knowledge discovery
published pages: , ISSN: , DOI:

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The information about "KDD-CHASER" are provided by the European Opendata Portal: CORDIS opendata.

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