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<p style="text-align: justify;">As it has been suggested, libraries and librarians can play a significant part in the development of Open Science, and several roles and measures have been identified for the different facets of Open Science (Open Access, Open Data, Open Educational Resources, Citizen Science, etc.) However, there is no doubt that currently the focus is primarily on the &ldquo;data&rdquo; and its management.</p>
<p style="text-align: justify;">Research Data Management (RDM) refers to &ldquo;<em>the storage, access and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded</em>&rdquo;. (CASRAI Dictionary, <a href="http://dictionary.casrai.org/Research_data_management">http://dictionar…;)</p>
<p style="text-align: justify;">Data lifecycle models can provide a framework for considering the opportunities available to library services in the sharing of research data, as it has been proposed by (<a href="https://www.fosteropenscience.eu/node/1431#stuart">Stuart, 2014</a>) on the basis of the UK Data Archive research data lifecycle (<a href="https://www.ukdataservice.ac.uk/manage-data/lifecycle">https://www.ukda…;) (see figure 5), or by the University of Virginia Library and the <em>Steps in the Data Life Cycle</em> (<a href="http://data.library.virginia.edu/data-management/lifecycle">http://data…;).</p>

<img src="/sites/default/files/images/UKDataLifeCycle_1.png" alt="Figure 5. UK Data Archive Research Data LifeCycle" />

**Figure 5. UK Data Archive Research Data LifeCycle ([https://www.ukdataservice.ac.uk/manage-data/lifecycle](https://www.ukdataservice.ac.uk/manage-data/lifecycle))**

<p style="text-align: justify;">The argument for libraries&rsquo; role in RDM can also be linked to the data issues or characteristics that research data must have and that represent opportunities for libraries and data centers. This has been highlighted by the <em>ODE Report on Integration of Data and Publications</em> (<a href="https://www.fosteropenscience.eu/node/1431#reilly">Reilly et al., 2011</a>) (see table below).</p>

<table>
<tbody>
<tr>
<td width="216">
<p><strong>Data Issue</strong></p>
</td>
<td width="673">
<p><strong>Libraries and data centres opportunities </strong></p>
</td>
</tr>
<tr>
<td rowspan="2" width="216">
<p>Availability</p>
</td>
<td width="673">
<p>Lower barriers to researchers to make their data available</p>
</td>
</tr>
<tr>
<td width="673">
<p>Integrate data sets into retrieval services</p>
</td>
</tr>
<tr>
<td rowspan="3" width="216">
<p>Findability</p>
</td>
<td width="673">
<p>Support of persistent identifiers</p>
</td>
</tr>
<tr>
<td width="673">
<p>Engage in developing common meta-description schemas and common citation practices</p>
</td>
</tr>
<tr>
<td width="673">
<p>Promote use of common standards and tools among researchers</p>
</td>
</tr>
<tr>
<td rowspan="3" width="216">
<p>Interpretability</p>
</td>
<td width="673">
<p>Support crosslinks between publications and datasets</p>
</td>
</tr>
<tr>
<td width="673">
<p>Provide and help researchers understand meta-descriptions of datasets</p>
</td>
</tr>
<tr>
<td width="673">
<p>Establish and maintain a knowledge base about data and their context</p>
</td>
</tr>
<tr>
<td rowspan="3" width="216">
<p>Re-usability</p>
</td>
<td width="673">
<p>Curate and preserve datasets</p>
</td>
</tr>
<tr>
<td width="673">
<p>Archive software needed for re-analysis of data</p>
</td>
</tr>
<tr>
<td width="673">
<p>Be transparent about conditions under which data sets can be re-used (expert knowledge needed, software needed)</p>
</td>
</tr>
<tr>
<td rowspan="2" width="216">
<p>Citability</p>
</td>
<td width="673">
<p>Engage in establishing uniform data citation standards</p>
</td>
</tr>
<tr>
<td width="673">
<p>Support and promote persistent identifiers</p>
</td>
</tr>
<tr>
<td rowspan="4" width="216">
<p>Curation /Preservation</p>
</td>
<td width="673">
<p>Transparency about curation of submitted data</p>
</td>
</tr>
<tr>
<td width="673">
<p>Promote good data management practice</p>
</td>
</tr>
<tr>
<td width="673">
<p>Collaborate with data creators</p>
</td>
</tr>
<tr>
<td width="673">
<p>Instruct researchers on discipline specific best practices in data creation (preservation formats, documentation of experiment,&hellip;)</p>
</td>
</tr>
</tbody>
</table>
<p style="text-align: justify;">&nbsp;</p>
<p style="text-align: justify;">Among the vast literature about the role of libraries and Research Data Management, and the good number of resources already available to help librarians to fulfil this role, we would like to highlight, as a general framework for action, the <strong>LIBER 10 Recommendation on Getting Started in RDM</strong> (<a href="https://www.fosteropenscience.eu/node/1431#christensen">Christensen-Dal… et al. 2012</a>):</p>

1. Offer research data management support, including data management plans for grant applications, intellectual property rights advice and information materials. Assist faculty with data management plans and the integration of data management into the curriculum.
2. Engage in the development of metadata and data standards and provide metadata services for research data.
3. Create Data Librarian posts and develop professional staff skills for data librarianship.
4. Actively participate in institutional research data policy development, including resource plans. Encourage and adopt open data policies where appropriate in the research data life cycle.
5. Liaise and partner with researchers, research groups, data archives and data centers to foster an interoperable infrastructure for data access, discovery and data sharing.
6. Support the lifecycle for research data by providing services for storage, discovery and permanent access.
7. Promote research data citation by applying persistent identifiers to research data.
8. Provide an institutional Data Catalogue or Data Repository, depending on available infrastructure.
9. Get involved in subject specific data management practice.
10. Offer or mediate secure storage for dynamic and static research data in co-operation with institutional IT units and/or seek exploitation of appropriate cloud services.

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Authors: Gema Bueno de la Fuente
Publication year: 2016
Language: English (EN)
Level of knowledge: Introductory: no previous knowledge is required
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