Life Cycle
The concrete tasks within research data management depend on the research data's life cycle.
Model of the Life Cycle of Research Data
Within the framework of the German WissGrid Projekt a simplified model was created based on the Curation Lifecycle Model by the Digital Curation Centre that is suitable for when individuals first start thinking about research data management.
Tasks in the Life Cycle of Research Data
Graphic: Tasks in the Life Cycle of Research Data (Source: WissGrid (PDF))
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Planning and Creation
Foundation of data management: Accruing data must be standardized. Based on this data, the correct standards must be selected to describe and store the data. -
Selection and Analysis
Analysis of the data with consideration for the storage required: From both an objective and economic perspective, it doesn't make sense to archive accruing data for a project permanently. A conscious decision ensures the replicability of the research data. -
Transfer
Research data that should be stored long term, must be transferred to a suitable storage environment. Steps include selecting a suitable repository, the transfer itself, and the fulfillment of the required metadata. -
Storage
Data storage is the core task of data management. Crucial paramters to consider include the size, number of datasets, and access frequency. -
Maintenance Measures
In order to ensure long term availability and re-usability, it may be necessary to make adjustments due to technological developments. -
Access and Use
Regulations are necessary so that data can be used internally by the institute or externally by others.
Additional Requirements Spanning the Life Cycle
There are requirements that span the lify cycle that should be considered in addition to those aspects dependent on the life cycle.
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Law and Ethics
Consideration should particularly given for the following: the protection of personal data, copyright, licensing of research data, and confidentiality. -
Financing
Long term financing for the infrastructure must be insured. -
Concepts
Research data management must include metadata and indentifiers. Comprehensive concepts are necessary if the data is to be re-used.