2023
2023-05-31
10.17192/bfdm.2023.3.8562
urn:nbn:de:hebis:04-0008-2023-311-85622
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Das Forschungsdatenzentrum der Universität Hamburg
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The more recent discussion of research data practices at relevant conferences, workshops and respective publications suggest substantially different foci of problems and solutions in managing data between scientific disciplines. There seems to be a particularly profound gap in natural science and humanities whereas social and life sciences are placed somewhere in between. Indeed data centers tailored to the specific needs of a single discipline (physics, chemistry, climate studies) are numerous in science and tend to be nearly absent for a specific humanities subject. While the former ask for and report solutions on scaling up (larger quantities of data can be run by the same application) and scaling out (larger quantities of data can use the same infrastructure), the latter are concerned with the heterogeneity of relatively small amounts of data (long-tail problem) and a divergence of agreed standards; something we may term as cross scaling. In either case, an efficiency problem has to be solved. On the one hand, huge amounts of data have to be handled within an acceptable time frame, on the other hand, many different applications with diverse functionalities have to be handled with an acceptable number of resources.+nbsp;
We would like to argue here that independent from the discipline either optimization problem should be addressed. Throughout the last decade, we have also observed that projects in science diversify and prefer individualized solutions which additionally hints at increasing data heterogeneity in natural science as well while, at the same time, some humanities projects produce petabytes of data. To show the necessity of a differentiated approach, the research data center of Universität Hamburg is offered as a case in point. The evolution of the center specialized in humanities projects to a research data center offering services for the whole university whereas other disciplinary data centers continue to exist side by side illustrates the entire range of tasks of data stewardship. It includes the continuous development of services while getting more and more involved in natural science projects as well as task sharing and communication with other data institutions. A core asset to understand the requirements of each discipline is a multidisciplinary team. Yet, the main organizing principle of the offered services centers around the stages of the data life cycle (1. data creation and deposit, 2. managing active data, 3. data repositories and archives, 4. data catalog and registries). The interdigitation of these stages is paramount in the long term strategy.
Open Access
Data Literacy
Forschungsdatenlebenszyklus
Forschungsrepositorium
Forschungsinformation
https://doi.org/10.17192/bfdm.2023.3.8562
Beiträge aus dem Workshop "Data Stewardship goes Germany" der FDM-AG der TU9-Allianz
2023
urn:nbn:de:hebis:04-0008-2023-3110
2023, 3
2626-7489
2947344-5
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Forschungsdatenmanagement
Research Data Management
AG Forschungsdaten
urn:nbn:de:hebis:04-00084
Bausteine Forschungsdatenmanagement
Periodical
Deutschhausstraße 9, 35037 Marburg
Marburg
Philipps-Universität Marburg
3
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PeriodicalPart
2023-07-14
Hagen
Peukert
Peukert, Hagen
Sylvia
Melzer
Melzer, Sylvia
Juliane
Jacob
Jacob, Juliane
Iris
Vogel
Vogel, Iris
Kai
Wörner
Wörner, Kai
Steffen
Grünler
Grünler, Steffen
Lisa
Brase
Brase, Lisa
Alexander
Heinrich
Heinrich, Alexander
Stefan
Thiemann
Thiemann, Stefan
Open Access
2023-05-31
Data Literacy
2023
The more recent discussion of research data practices at relevant conferences, workshops and respective publications suggest substantially different foci of problems and solutions in managing data between scientific disciplines. There seems to be a particularly profound gap in natural science and humanities whereas social and life sciences are placed somewhere in between. Indeed data centers tailored to the specific needs of a single discipline (physics, chemistry, climate studies) are numerous in science and tend to be nearly absent for a specific humanities subject. While the former ask for and report solutions on scaling up (larger quantities of data can be run by the same application) and scaling out (larger quantities of data can use the same infrastructure), the latter are concerned with the heterogeneity of relatively small amounts of data (long-tail problem) and a divergence of agreed standards; something we may term as cross scaling. In either case, an efficiency problem has to be solved. On the one hand, huge amounts of data have to be handled within an acceptable time frame, on the other hand, many different applications with diverse functionalities have to be handled with an acceptable number of resources.+nbsp;
We would like to argue here that independent from the discipline either optimization problem should be addressed. Throughout the last decade, we have also observed that projects in science diversify and prefer individualized solutions which additionally hints at increasing data heterogeneity in natural science as well while, at the same time, some humanities projects produce petabytes of data. To show the necessity of a differentiated approach, the research data center of Universität Hamburg is offered as a case in point. The evolution of the center specialized in humanities projects to a research data center offering services for the whole university whereas other disciplinary data centers continue to exist side by side illustrates the entire range of tasks of data stewardship. It includes the continuous development of services while getting more and more involved in natural science projects as well as task sharing and communication with other data institutions. A core asset to understand the requirements of each discipline is a multidisciplinary team. Yet, the main organizing principle of the offered services centers around the stages of the data life cycle (1. data creation and deposit, 2. managing active data, 3. data repositories and archives, 4. data catalog and registries). The interdigitation of these stages is paramount in the long term strategy.
Forschungsdatenlebenszyklus
German
article
Auf dem Weg zu einem gemeinsamen Verständnis im Umgang mit Forschungsdaten in den Natur-, Sozial- und Geisteswissenschaften
Universitätsbibliothek Marburg
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Das Forschungsdatenzentrum der Universität Hamburg
2023-05-31
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2024-01-09
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