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INVEST Data Group - Data services for the research flagship INVEST

Authors: Kaarakainen, Meri-Tuulia;

INVEST Data Group - Data services for the research flagship INVEST

Abstract

The Inequalities, Interventions, and New Welfare State (INVEST) research flagship aims at increasing well-being of Finnish society during childhood, youth and early adulthood by preventing psycho-social risks compromising such development through innovative interventions. INVEST is a joint project of the University of Turku and the National Institute for Health and Welfare. The research groups under the Flagship are supported by a Data Group with the following strategic goals: (1) Promotion of the widespread availability and usability of data among the INVEST researchers, (2) Establishment of the discipline-specific research infrastructures and data management practices for the INVEST flagship, (3) Promotion of data expertise and strengthening the competence cluster among INVEST research groups and more widely among researchers, (4) Ensuring wide availability of registry data and raising awareness of its importance for the competitiveness of Finnish population, welfare and and health, and social science research (5) Supporting the implementation of the FAIR principles (i.e., findability, accessibility, interoperability, and re-usability) and (6) Promotion of practices that enhance the role of data and methods as research merits and outputs. The poster presents the goals, principles and operating models of this newly established Data Group. It describes the general information architecture and service offering that is currently being developed for the INVEST flagship researchers. For some data sets, the Data Group covers the entire data management life-cycle, while for others, the offering is limited to guidance, licensing processes, and other practical support. The Data Group is responsible, among other things, for managing primary data, extracting data from databases, describing and modulating data for research purposes, and producing codebooks and cataloging the data sets to improve discoverability and usability of research data. Efforts will be made to promote teamwork practices for collaborative data processing and analysis, such as version control and sharing of guidelines, documentation, and scripts among researchers and, later, to the general public as specific research outputs.

Poster in session Strategies to Implement RDM Services in CODATA-Helsinki Workshop on FAIR RDM in Institutions 2019

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Keywords

Data services, data management, research data

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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