This document discusses the future of information infrastructures and open science. It notes that for effective communication, replication and repurposing of scientific knowledge, data and metadata must be accessible, intelligible, assessable and reusable. Open science involves making the scientific record free of financial barriers, quality-assured, archived and available for any purpose or reuse. However, open data policies must be audience sensitive and consider who can access and use the data. The role of libraries is shifting from being collections-centered to engagement-centered by building services around user workflows and participating in the entire research process.

1. KIT-BIBLIOTHEK
KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholz-Gemeinschaft
Informationsinfrastrukturen - wie geht es weiter?
Frank Scholze
GoportisWorkCamp Bremen, 4.11.2014

2. Data Driven Science
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dder
Quelle: Geoffrey Boulton, Talk at Open Science Days Berlin, 14.10.2014 Jisc (2012) Activity Data: Delivering benefits from the data deluge

3. dd
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4. Reproduzierbarkeit
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5. Glaubwürdigkeit
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6. Crowd Sourcing Science
“Its like driving a car whilst normal research is like pushing it” (Tim Gowers)
Überschneidungen mit Citizen Science
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7. Science 2.0
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http://commons.wikimedia.org/wiki/File:Current_vs_emerging_methods_of_science_in_terms_of_pathways.png

8. Open Science
“Open science is the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.” Michael Nielsen
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Quelle: http://openscienceasap.org/open-science/

9. 9 4.11.2014 KIT-Bibliothek
Quelle: Geoffrey Boulton, Talk at Open Science Days Berlin, 14.10.2014

10. ICSU - Open Science Declaration
The scientific record should be:
free of financial barriers for any researcher to contribute to;
free of financial barriers for any user to access immediately on publication;
made available without restriction on reuse for any purpose, subject to proper attribution;
quality-assured and published in a timely manner;
archived and made available in perpetuity.
Empfehlungen
Datensupplemente zu Textpublikationen zitierbar machen
Offene Lizenzierung von Forschungsdaten, um die Nachnutzung zu erleichtern
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http://www.icsu.org/general-assembly/news/ICSU%20Report%20on%20Open%20Access.pdf

11. Open science is more than disclosure
For effective communication, replication and repurposing we need intelligent openness
Data and meta-data must be:
Accessible
Intelligible
Assessable
Re-usable
Only when these four criteria are fulfilled are data properly open.
But, intelligent openness must be audience sensitive.
Open data to whom and for what?
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The Royal Society. (2012). Science as an open enterprise. http://royalsociety.org/uploadedFiles/Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf

12. Outside in
1.
User builds workflow around library services
2.
Towards a centered network presence
3.
Locally assemble externally acquired colls
4.
Discovery happens in the library
5.
Expertise hidden
6.
Configure space around collections
Inside out
1.
Library services built around user workflows
2.
Towards a decentered network presence
3.
Engage with creation, management, use and sharing of all information resources
4.
Discovery happens elsewhere
5.
Expertise visible
6.
Configure space around engagement
Quelle: Lorcan Dempsey: The Inside Out Library Redux, University of Melbourne, 11 April 2013 4.11.2014 KIT-Bibliothek 12

13. Der wissenschaftliche Wertschöpfungsprozess
KIT-Bibliothek
Learning Environments
Learning Management Systems
Submission and Review
Grant Application
Research Networks
Research Environments
Text and Data Mining 13 4.11.2014
Reference Management Systems
Resource Discovery Systems
Publication and Preprint Repositories
Enhanced PDF
Research Data Repositories
CRIS
Text Processing Systems
Research Tools
Methods and Experiments
Text Processing Systems
MOOCs
Credit and Impact
Publisher Plattforms

14. Wouter Haak
Elsevier, VP Product Strategy
LIBER, Riga, 2014
Workflow is the new content
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15. Research Operating System
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16. Wie geht es weiter?
Konkretisierung
Konzeptionell
technisch
organisatorisch
kulturell
Rollen und Markt: Clusterbildung; den richtigen Rahmen finden
Struktur: Bottom up – top down
Nachfrageorientierung statt Angebotsorientierung
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17. Der wissenschaftliche Wertschöpfungsprozess
KIT-Bibliothek
Learning Environments
Learning Management Systems
Submission and Review
Grant Application
Research Networks
Research Environments
Text and Data Mining 17 4.11.2014
Reference Management Systems
Resource Discovery Systems
Publication and Preprint Repositories
Enhanced PDF
Research Data Repositories
CRIS
Text Processing Systems
Research Tools
Methods and Experiments
Text Processing Systems
MOOCs
Credit and Impact
Publisher Plattforms
Lizenzen
Open Access
Forschungsdaten

18. Wer stark ist muss auch gut sein
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