A generic research data infrastructure for long tail research data management

被引：1

作者：

Latif A. ^{[1
]}

Limani F. ^{[1
]}

Tochtermann K. ^{[1
]}

机构：

[1] ZBW – Leibniz Information Center for Economics, Kiel/Hamburg

来源：

Data Science Journal | 2019年 / 18卷 / 01期

关键词：

Generic Research Data Infrastructure; Long Tail Content; Research Data; Research Data Management;

D O I：

10.5334/dsj-2019-017

中图分类号：

学科分类号：

摘要：

The advent of data intensive science has fueled the generation of digital scientific data. Undoubtedly, digital research data plays a pivotal role in transparency and re-producibility of scientific results as well as in steering the innovation in a research process. However, the main challenges for science policy and infrastructure projects are to develop practices and solutions for research data management which in compliance with good scientific standards make the research data discoverable, citeble and accessible for society potential reuse. GeRDI – the Generic Research Data (RD) Infrastructure – is such a research data management initiative which targets long tail content that stems from research communities belonging to different domain and research practices. It provides a generic and open software which connects research data infrastructures of communities to enable the investigation of multidisciplinary research questions. © 2019 The Author(s).

引用

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