Abstract
Information integration is an on-going challenge in data management and various approaches have been proposed in database research. New technologies and application areas create different requirements for integration systems. Research information management (RIM) is yet another challenge for data integration. RIM has many properties that are typical for data integration scenarios: many data sources, various modeling languages and data models, heterogeneity in syntax and semantics. Furthermore, many stakeholders are involved in RIM, usually with diverting goals. The combination of these properties makes RIM a particular difficult integration problem.In this paper, we discuss the applicability of data integration approaches to research information management. In particular, we want to highlight the lessons which have been learned in data integration in the recent years. Early approaches in data integration focused on the data models and the problems with schema integration. Recent work rather concentrates on the mappings between models and integration processes. Our main argument in this paper is that mappings should be also considered as key objects in research information systems.
Highlights
Management of research information has become an important issue for universities, research organizations, funding and government organizations
We do not want to provide additional arguments for this discussion; we focus in this paper on the technical aspects of research information management and especially the standardization of a basic data model for research information
The context of the work presented in this paper is the German project for developing a basic data model for research information †, which has been initiated by the German Council of Science and Humanities (Wissenschaftsrat) and which is funded by the Federal Ministry for Education and Research
Summary
Management of research information has become an important issue for universities, research organizations, funding and government organizations. The context of the work presented in this paper is the German project for developing a basic data model for research information † (called the ‘core dataset’, ‘Kerndatensatz Forschung’ in German, KDSF in short in the following), which has been initiated by the German Council of Science and Humanities (Wissenschaftsrat) and which is funded by the Federal Ministry for Education and Research. Within this project, several working groups discuss different aspects of the data model, e.g., definitions of the main elements, a classification of subjects, definitions for bibliographic data, and the definition of formal data models and interfaces.
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