On ontology based data integration: problems and solutions

The measuring of research results can be used in different ways e.g. for assignment of research grants and afterwards for evaluation of project’s results. It can be used also for recruiting or promoting research institutions’ staff. Because of a wide usage of such measurement, the selection of appropriate measures is important. At the same time there does not exist a common view which metrics should be used in this field, moreover many existing metrics that are widely used are often misleading due to different reasons, e.g. computed from incomplete or faulty data, the metric’s computation formula may be invalid or the computation results can be interpreted wrongly. To produce a good framework for research evaluation, the mentioned problems must be solved in the best possible way by integrating data from different sources to get comprehensive view of academic institutions’ research activities and to solve data quality problems. We will present a data integration system that integrates university information system with library information system and with data that are gathered through API from Scopus and Web of Science databases. Data integration problems and data quality problems that we have faced are described and possible solutions are presented. Metrics that are defined and computed over these integrated data and their analysis possibilities are also discussed.

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Integrating Heterogeneous Biomedical Data for Cancer Research: the CARPEM infrastructure

Applied Clinical Informatics ◽

10.4338/aci-2015-09-ra-0125 ◽

2016 ◽

Vol 07 (02) ◽

pp. 260-274 ◽

Cited By ~ 18

Author(s):

Vincent Canuel ◽

Hector Countouris ◽

Pierre Laurent-Puig ◽

Anita Burgun ◽

Bastien Rance

Keyword(s):

Cancer Research ◽

Data Integration ◽

Translational Research ◽

Data Access ◽

Biomedical Data ◽

Research Platform ◽

Heterogeneous Nature ◽

Three Layer Architecture ◽

Technical Principles ◽

Integration Problems

SummaryCancer research involves numerous disciplines. The multiplicity of data sources and their heterogeneous nature render the integration and the exploration of the data more and more complex. Translational research platforms are a promising way to assist scientists in these tasks. In this article, we identify a set of scientific and technical principles needed to build a translational research platform compatible with ethical requirements, data protection and data-integration problems. We describe the solution adopted by the CARPEM cancer research program to design and deploy a platform able to integrate retrospective, prospective, and day-to-day care data. We designed a three-layer architecture composed of a data collection layer, a data integration layer and a data access layer. We leverage a set of open-source resources including i2b2 and tranSMART.Citation: Rance B, Canuel V, Countouris H, Laurent-Puig P, Burgun A. Integrating heterogeneous biomedical data for cancer research: the CARPEM infrastructure.

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