1. Libraries as Data-Centers for the Arts and Humanities
SciDataCon, Denver, September 2016

2. Testing Libraries as Data Centers
No worries, no ISO 9000 or ISO/IEC :2016
But: FAIR Principles
Findable
Accessible
Interoperable
Re-usable (Reproducible?)
There is more
Sustainable
Resilient / Distributed
Semantic „Aware“
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3. A simple example: DFG Digitization Programme
A structured funding programme for print heritage, distributed in Germany
Organized by centuries, mandatory guidleines, since several years
Titles
Pages
VD16
c. 14 Mio.
VD17
c. 45 Mio.
VD18
c. 90 Mio.
May not sound overwhelming, but it represents huge assetts
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5. A simple example: DFG Digitization Programme >> Findable
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.
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6. A simple example: DFG Digitization Programme >> Findable
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.
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7. A simple example: DFG Digitization Programme >> Findable
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.
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8. A simple example: DFG Digitization Programme >> Accesible
A1 (meta)data are retrievable by their identifier using a standardized communications protocol. A1.1 the protocol is open, free, and universally implementable. A1.2 the protocol allows for an authentication and authorization procedure, where necessary. A2 metadata are accessible, even when the data are no longer available.
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9. A simple example: DFG Digitization Programme >> Interoperable
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles. I3. (meta)data include qualified references to other (meta)data.
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10. A simple example: DFG Digitization Programme >> Reusable
R1. meta(data) have a plurality of accurate and relevant attributes. R1.1. (meta)data are released with a clear and accessible data usage license. R1.2. (meta)data are associated with their provenance. R1.3. (meta)data meet domain-relevant community standards.
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... and now the actual data...
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12. Transcribed digitized images yield text corpora
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13. e.g. highly structured text as TEI
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14. Algorithmic Analysis allows use-cases

15. Dozens of use cases in Germany (and beyond)
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Summary
Libraries are ‚natural‘ data centers for research data management
Libraries implement FAIR-Principles (even before their existence)
Additionally libraries implement advanced data management principles
Sustainability: institutions and funding already in place
Resilience/Distribution: a culture of division of labour – nationally & internationally
Semantic ‚aware‘: culture of content & people beyond the bits & bytes
Research Infrastructures, e.g. DARIAH/TextGrid boost actual data re-use
How to build Research Infrastructures for the Sciences in libraries?
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17. Thank you for your attention