Strategien zur Vernetzung von Biobanken: Klassifizierung verschiedener Ansätze zur Probensuche und Ausblick auf die Zukunft in der BBMRI-ERIC = Strategies for biobank networks : classification of different approaches for locating samples and an outlook on the future within the BBMRI-ERIC
BackgroundMedical research projects often require more biological material than can be supplied by a single biobank. For this reason, a multitude of strategies support locating potential research partners with matching material without requiring centralization of sample storage.ObjectivesClassificat...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | German English |
| Published: |
2016
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| In: |
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Year: 2016, Volume: 59, Issue: 3, Pages: 373-378 |
| ISSN: | 1437-1588 |
| DOI: | 10.1007/s00103-015-2299-y |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1007/s00103-015-2299-y Verlag, Volltext: https://link.springer.com/article/10.1007/s00103-015-2299-y 
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| Author Notes: | Martin Lablans, Dennis Kadioglu, Sebastian Mate, Ines Leb, Hans-Ulrich Prokosch, Frank Ückert |
| Summary: | BackgroundMedical research projects often require more biological material than can be supplied by a single biobank. For this reason, a multitude of strategies support locating potential research partners with matching material without requiring centralization of sample storage.ObjectivesClassification of different strategies for biobank networks, in particular for locating suitable samples. Description of an IT infrastructure combining these strategies.Materials and methodsExisting strategies can be classified according to three criteria: (a) granularity of sample data: coarse bank-level data (catalogue) vs. fine-granular sample-level data, (b) location of sample data: central (central search service) vs. decentral storage (federated search services), and (c) level of automation: automatic (query-based, federated search service) vs. semi-automatic (inquiry-based, decentral search). All mentioned search services require data integration. Metadata help to overcome semantic heterogeneity.ResultsThe “Common Service IT” in BBMRI-ERIC (Biobanking and BioMolecular Resources Research Infrastructure) unites a catalogue, the decentral search and metadata in an integrated platform. As a result, researchers receive versatile tools to search suitable biomaterial, while biobanks retain a high degree of data sovereignty.ConclusionsDespite their differences, the presented strategies for biobank networks do not rule each other out but can complement and even benefit from each other. |
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| Item Description: | First Online: 11 January 2016 Gesehen am 13.06.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1437-1588 |
| DOI: | 10.1007/s00103-015-2299-y |