Development and implementation of a data citation metrics system
Sharing research data is developing towards a new priority in scientific discourse. It moved from a bothersome task to a scientific asset. Concepts, like FAIR research data (findable, accessible, interoperable, re-usable), data publication, open data is becoming an essential part of scientific work.
This thesis will focus to investigate, develop and implement metrics systems to measure the impact of published scientific data. Classic metrics like, download volume, click count, search hits etc. should be extended and matched with classic literature citation metrics, like H-index system to fill the gap between data publications and manuscript citations.
The focus of this thesis project is the evaluation of existing approaches for data citation and usage metrics and the development of a suitable concept for existing data publication infrastructure of the IPK, which based on the e!DAL infrastructure. The final part of thesis is than the implementation and integration of the previously designed concept into the PGP-Repository of the IPK. Some experience with Java and Object-Oriented Programming as well as general understanding of Relational Databases/SQL is needed. Basic knowledge about HTTP/REST is also recommended. Experience with version control systems (Git, SVN) and Build Management Tools (MVN, Gradle) can be helpful, but is not mandatory.
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If you are interested in this topic, please contact Dr. Daniel Arend for further information.