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Open Data


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Open Science

Open Data - free data with free licenses

What is Open Data?1

Open Data is data that may be used, disseminated and reused by anyone for any purpose. The only restriction is that the creator must be named.

Open data must meet the following requirements:

availability and accessibility

Data must be provided as a whole and at no more than a reasonable one-time reproduction cost, and should be downloadable via the Internet without charge. Data must be provided in an appropriate and editable format.

reuse and dissemination

Data must be provided under conditions that allow reuse and dissemination, also as part of a collection made from works from different sources.

universal contribution

Everyone must be allowed to use the licensed data, to create derivatives of the licensed data and to distristribute such derivatives under the same terms of the original data. The data license must not discriminate against any person, group or purpose. E.g. restrictions to commercial usage or restrictions to specific usage purposes is not allowed.

Research data as a part of open data2

Research data are data that are collected or generated during the research process. They can include quantitative measuring data, survey data, statistical data, qualitative data like interview transliterations, notes from field research, audio and visual data or software and much more. Research data may become part of open data. Researchers, scientific communities and the whole society can benefit from open research data. Besides, in terms of the scientific and scholarly Code of conduct data may be reusable and, therefore, verifiable. This is already constituent to research funder‘s requirements, e.g. the DFG. They say that research data must be made accessible as FAIR (findable, accessible, interoperable, reusable) data while considering legal restrictions.

The Fair data principles3

Grafische Darstellung

The FAIR data principles by GoFAIR which many research funder‘s relate to define principles for the setting up of research data infrastructure:

  • Findable: Data and supplementary materials have sufficiently rich metadata and a unique and persistent identifier.
  • Accessible: Metadata and data are understandable to humans and machines. Data is deposited in a trusted repository.
  • Interoperable: Metadata use a formal, accessible, shared, and broadly applicable language for knowledge representation.
  • Reusable: Data and collections have a clear usage licenses and provide accurate information on provenance.

Research Data Management – Lifecycle

The research data lifecycle illustrates the management of research data from searching for available data and collecting data to archiving and reusing data.

Note: Starting the video will forward information to Youtube. Further information can be found here:

Examples of open data / research data at Chemnitz University of Technology

Librarians of the University Library share selected pieces of their work freely accessible and reusable via Wikimedia Commons.

Wikimedia Commons

Wikimedia Commons

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Digital copies of rare books from the University Library are made available under open licenses (metadata CC0, pictures CC-BY-SA and PD).

Digitale Sammlung

Free licenses

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The University Library took part in Kultur-Hackathon Coding da Vinci Ost in Leipzig and contributed two open data collections.

Library newsletter 01/2018 (German)

Coding Da Vinci

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University Library assembles knowledge on research data management in its Open Science-Team

Open Science team

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Services of the University Library

Darstellung der Serviceleitungen der UB im Forschungsprozess

You find further on our website for research data.


1 Open Knowledge International: Open Definition 2.1., last access: August 20 2019

class="linkextern">, letzter Zugriff: 9. Mai 2019

2 Knight, Gareth: Prepearing Data for Sharing. The FAIR principles.Vortrag auf dem ADMIT Networking Meeting am 1. Dezember 2015., last access: Mai 9 2019

3 GO FAIR: Fair principles., last access: Mai 9 2019


Portrait: Anja Hähle
Anja Hähle
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