Richard Grunzke

Generic Metadata Handling in Scientific Data Life Cycles

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Kurzfassung in Englisch

Scientific data life cycles define how data is created, handled, accessed, and analyzed by users. Such data life cycles become increasingly sophisticated as the sciences they deal with become more and more demanding and complex with the coming advent of exascale data and computing. The overarching data life cycle management background includes multiple abstraction categories with data sources, data and metadata management, computing and workflow management, security, data sinks, and methods on how to enable utilization. Challenges in this context are manifold. One is to hide the complexity from the user and to enable seamlessness in using resources to usability and efficiency. Another one is to enable generic metadata management that is not restricted to one use case but can be adapted with limited effort to further ones.

Metadata management is essential to enable scientists to save time by avoiding the need for manually keeping track of data, meaning for example by its content and location. As the number of files grows into the millions, managing data without metadata becomes increasingly difficult. Thus, the solution is to employ metadata management to enable the organization of data based on information about it. Previously, use cases tended to only support highly specific or no metadata management at all. Now, a generic metadata management concept is available that can be used to efficiently integrate metadata capabilities with use cases.

The concept was implemented within the MoSGrid data life cycle that enables molecular simulations on distributed HPC-enabled data and computing infrastructures. The implementation enables easy-to-use and effective metadata management. Automated extraction, annotation, and indexing of metadata was designed, developed, integrated, and search capabilities provided via a seamless user interface. Further analysis runs can be directly started based on search results. A complete evaluation of the concept both in general and along the example implementation is presented. In conclusion, generic metadata management concept advances the state of the art in scientific date life cycle management.

weitere Metadaten

Generic Metadata Handling, Scientific Data Life Cycles
DDC Klassifikation004
RVK KlassifikationST 265
HochschuleTechnische Universität Dresden
FakultätFakultät Informatik
ProfessurProfessur für Rechnerarchitektur
BetreuerProf. Dr. Wolfgang E. Nagel
GutachterProf. Dr. Wolfgang E. Nagel
Prof. Dr. Achim Streit
Tag d. Einreichung (bei der Fakultät)16.12.2015
Tag d. Verteidigung / Kolloquiums / Prüfung12.04.2016
Veröffentlichungsdatum (online)11.05.2016
persistente URNurn:nbn:de:bsz:14-qucosa-202070

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