<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2011</id>
    <completedYear>2018</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>11</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Standardisation in life-science research - Making the case for harmonization to improve communication and sharing of data amongst researchers</title>
    <abstract language="eng">Modern, high-throughput methods for the analysis of genetic information, gene and metabolic products and their interactions offer new opportunities to gain comprehensive information on life processes. The data and knowledge generated open diverse application possibilities with enormous innovation potential. To unlock that potential skills in generating but also properly annotating the data for further data integration and analysis are needed. The data need to be made computer readable and interoperable to allow integration with existing knowledge leading to actionable biological insights. To achieve this, we need common standards and standard operating procedures as well as workflows that allow the combination of data across standards. Currently, there is a lack of experts who understand the principles and possess knowledge of the principles  and  relevant  tools.  This  is  a  major barrier hindering the implementation of FAIR (findable, accessible, interoperable and reusable) data principles and the actual reusability of data. This is mainly due to insufficient and unequal education of the scientists and other stakeholders involved in producing and handling big data in  life  science  that  is inherently varied and complex  in nature,  and  large  in  volume. Due  to  the  interdisciplinary  nature  of  life  science research,  education within  this  field faces numerous hurdles including institutional barriers, lack of local availability of all required expertise, as well as lack of appropriate teaching material and appropriate adaptation of curricula.</abstract>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-20118</identifier>
    <enrichment key="opus.import.date">2025-02-27T11:43:55+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">sword</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.29007/4xkd</enrichment>
    <enrichment key="SourceTitle">Hollmann, S., Regierer, B., D’Elia, D., Gruden, K., Baebler, Š., Frohme, M., Pfeil, J., Sezerman, U.O., Evelo, C.T., Ehrhart, F., Huppertz, B., Bongcam-Rudloff, E., Trefois, C., Gruca, A., Duca, D., Colotti, G., Merino-Martinez, R., Ouzounis, C.A., Hunewald, O., He, F., &amp; Kremer, A. (2018). Standardisation in life-science research - Making the case for harmonization to improve communication and sharing of data amongst researchers. EasyChair Preprints.</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Susanne Hollmann</author>
    <author>Babette Regierer</author>
    <author>Domenica D'Elia</author>
    <author>Marcus Frohme</author>
    <author>Kristina Gruden</author>
    <author>Juliane Pfeil</author>
    <author>Spela Baebler</author>
    <author>Ugur Sezerman</author>
    <author>Chris T. Evelo</author>
    <author>Friederike Erhart</author>
    <author>Berthold Huppertz</author>
    <author>Erik Bongcam-Rudloff</author>
    <author>Christophe Trefois</author>
    <author>Aleksandra Gruca</author>
    <author>Deborah Duca</author>
    <author>Gianni Colotti</author>
    <author>Roxana Merino-Martinez</author>
    <author>Christos Ouzounis</author>
    <author>Oliver Hunewald</author>
    <author>Feng He</author>
    <author>Andreas Kremer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FAIR data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>standardization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>interoperability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>standard operating procedures (SOPs)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quality management (QM)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quality control (QC)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>education</value>
    </subject>
    <collection role="ddc" number="005">Computerprogrammierung, Programme, Daten</collection>
    <collection role="ddc" number="570">Biowissenschaften; Biologie</collection>
    <collection role="institutes" number="">Fachbereich Ingenieur- und Naturwissenschaften</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="Import" number="import">Import</collection>
    <collection role="green_open_access" number="2">Green Open Access</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/2011/EasyChair-Preprint-580.pdf</file>
  </doc>
</export-example>
