A Selection of Research Data Management Tools Throughout the Data Lifecycle
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In this document, several useful research data management tools are listed and described for each step of their research throughout the data lifecyle management.
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Data management comprises all disciplines related to handling data as a valuable resource. The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems.
In industry, product lifecycle management (PLM) is the process of managing the entire lifecycle of a product from its inception through the engineering, design and manufacture, as well as the service and disposal of manufactured products. PLM integrates people, data, processes, and business systems and provides a product information backbone for companies and their extended enterprises. The inspiration for the burgeoning business process now known as PLM came from American Motors Corporation (AMC).
Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance. On the macro level, data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called international data governance. This new field consists of "norms, principles and rules governing various types of data.
In recent years, funding agencies, governments, and international organization have issued a series of research data management and sharing policies, like the H2020 [1]. Researchers are encouraged or required to share their production in an open way, inclu ...
2019
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This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried ou ...
Managing research data throughout its lifecycle ensures its long-term value and prevents data from falling into digital obsolescence. Proper data management is a key prere- quisite for effective data sharing throughout the scientific community. This, in tu ...