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TOOLS FÜR DAS
MANAGEMENT VON
FORSCHUNGSDATEN
Workshop „Wege in die Köpfe“ des DFG-Projekts „EWIG -
Entwicklung von Workflowkomponenten für die
Langzeitarchivierung von Forschungsdaten in den
Geowissenschaften“
Berlin, 03.07.2014
Heinz Pampel, Deutsches GeoForschungsZentrum GFZ
TOOLS – EINE AUSWAHL
MATLAB R-Pakete GRASS GIS
Tools zur Analyse
von
Forschungsdaten
TOOLS – EINE AUSWAHL
MATLAB R-Pakete GRASS GIS
FileZilla
Tools zur Analyse
von
Forschungsdaten
Tools zum
Austausch von
„Daten“
TOOLS – EINE AUSWAHL
MATLAB R-Pakete GRASS GIS
FileZilla
LabArchives
Tools zur Analyse
von
Forschungsdaten
Tools zum
Austausch von
„Daten“
Tools zum
Management von
Forschungsdaten
TOOLS – EINE AUSWAHL
MATLAB R-Pakete GRASS GIS
FileZilla
LabArchives
Tools zur Analyse
von
Forschungsdaten
Tools zum
Austausch von
„Daten“
Tools zum
Management von
Forschungsdaten
Tools zur
dauerhaften
Zugänglichkeit von
Forschungsdaten
TOOLS – EINE AUSWAHL
Klump, J., & Bertelmann, R. (2013). D 8 Forschungsdaten. In R. Kuhlen, W. Semar, & D. Strauch
(Eds.), Grundlagen der praktischen Information und Dokumentation. Berlin: De Gruyter Saur.
doi:10.1515/9783110258264.575
•  „Building a sound infrastructure for data sharing,
preservation, and use is a challenge, but is in some
ways easier than changing a culture.“
•  „The leading reasons were insufficient time and lack
of funding.“
•  „These are difficult to solve, but systems that make it
quick and easy to share data without cost may help.“
INFRASTRUKTUR ALS ANREIZ
Tenopir, C. et al. (2011). Data Sharing by Scientists: Practices and
Perceptions. PLoS ONE, 6(6), e21101. doi:10.1371/journal.pone.0021101
INFRASTRUKTUR ALS ANREIZ
•  „Building a sound infrastructure for data sharing,
preservation, and use is a challenge, but is in some
ways easier than changing a culture.“
•  „The leading reasons were insufficient time and lack
of funding.“
•  „These are difficult to solve, but systems that make it
quick and easy to share data without cost may help.“
Tenopir, C. et al. (2011). Data Sharing by Scientists: Practices and
Perceptions. PLoS ONE, 6(6), e21101. doi:10.1371/journal.pone.0021101
INFRASTRUKTUR ALS ANREIZ
•  „A key finding is that incentives for data sharing have to
be developed. These have to be linked to the academic
incentive system as well as to the research assessment
schemes.“
•  „The technical barriers to share data have to be reduced
by simplifying data sharing workflows.“
•  „Several stakeholders, from publishers or data centres
to funders have to be involved in this process to
address researchers’ hesitation to manage their data
and make them available.“
Dallmeier-Tiessen, S.; et al. (2012): D6.1 Summary of the Studies,
Thematic Publications and Recommendations. Retrieved from doi.org/
10.5281/zenodo.8305
INFRASTRUKTUR ALS ANREIZ
•  „A key finding is that incentives for data sharing have to
be developed. These have to be linked to the academic
incentive system as well as to the research assessment
schemes.“
•  „The technical barriers to share data have to be reduced
by simplifying data sharing workflows.“
•  „Several stakeholders, from publishers or data centres
to funders have to be involved in this process to
address researchers’ hesitation to manage their data
and make them available.“
Dallmeier-Tiessen, S.; et al. (2012): D6.1 Summary of the Studies,
Thematic Publications and Recommendations. Retrieved from doi.org/
10.5281/zenodo.8305
RAHMENBEDINGUNGEN
Grafik: re3data.org
RAHMENBEDINGUNGEN
Grafik: re3data.org
RAHMENBEDINGUNGEN
•  Data Policies von Förderorganisationen
•  Europäische Kommission: HORIZON 2020
Horizon 2020 Annotated Model Grant Agreements. Version 1.6. 2 May 2014. Retrieved
from http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/amga/
h2020-amga_en.pdf
RAHMENBEDINGUNGEN
•  Data Policies von Förderorganisationen
•  Europäische Kommission: HORIZON 2020
Spichtinger, D & Ramjoué, C. (2014): Open Access and the Open Research Data Pilot
in H2020. EC Seminar. Retrieved from http://ec.europa.eu/information_society/
newsroom/cf/dae/document.cfm?action=display&doc_id=4602
RAHMENBEDINGUNGEN
•  Data Policies von Journals
•  Beispiel PLOS ONE
PLOS ONE
Öffentliches
Repositorium
Verlagsplattform
Sonstiges
re3data.org
•  Projektpartner:
•  Deutsches GeoForschungsZentrum
GFZ, Bibliothek und
Informationsdienste (LIS)
•  Humboldt-Universität zu Berlin,
Institut für Bibliotheks- und
Informationswissenschaft (IBI)
•  Instituts für Technologie (KIT),
KIT-Bibliothek
•  Förderorganisation:
•  Deutsche
Forschungsgemeinschaft
•  Phase 1: 2013-2014
•  Phase 2: 2014-2015
•  Diverse Kooperationspartner
Pampel, H. et al. (2013). Making Research Data Repositories Visible: The re3data.org
Registry. PLOS ONE, 8(11), e78080. doi:10.1371/journal.pone.0078080
re3data.org
•  Aufbau eines Verzeichnisses zur Beschreibung von
Forschungsdaten-Repositorien
•  Unterstützung für Forschende, Förderorganisationen und
Einrichtungen der Informationsinfrastruktur
•  Beitrag zur Weiterentwicklung der Forschungsdaten-
Repositorien (Standardisierung und Professionalisierung)
•  Nationaler Beitrag zur weltweiten Diskussion über die
Schaffung von offenen Forschungsdaten-Infrastrukturen
re3data.org
•  Version 1.0 (2012)
•  Resultat einer Bestandsaufnahme
•  http://doi.org/10.2312/re3.001
•  Version 2.0 (2012)
•  Ergebnis einer öffentlichen Konsultation
•  http://doi.org/10.2312/re3.002
•  http://www.re3data.org/schema/2-0/
•  Version 2.1 (2013)
•  Zusammenarbeit mit Kooperationspartnern
•  http://doi.org/10.2312/re3.004
•  http://www.re3data.org/schema/2-1/
•  Neue Version in Arbeit (2014) Vierkant, P., et al. (2013). Schema for the Description of Research
Data Repositories. Version 2.1. doi:10.2312/re3.004
re3data.org
simple
search box
filters
results
icons
re3data.org
re3data.org
re3data.org
re3data.org
re3data.org
•  Requirements
•  be run by a legal entity, such
as a sustainable institution
(e.g. library, university)
•  clarify access conditions to the
data and repository as well as
the terms of use
•  have an English graphical user
interface (GUI)
•  have focus on research data
Vierkant, P., et al. (2013). Schema for the Description of Research Data
Repositories. Version 2.1. doi:10.2312/re3.004
re3data.org
Vierkant, P., et al. (2013). Schema for the Description of Research
Data Repositories. Version 2.1. doi:10.2312/re3.004
re3data.org
http://www.re3data.org/2014/06/wikipedia-entry-for-re3data-org/
re3data.org
•  Kooperationen: Verlage
re3data.org
•  Kooperationen: Verlage
http://www.nature.com/sdata/data-policies/repositories
re3data.org
•  Kooperationen: Förderorganisationen
European Commisson. (2013). Guidelines on Open
Access to Scientific Publications and Research Data in
Horizon 2020. Retrieved from http://ec.europa.eu/
research/participants/data/ref/h2020/grants_manual/
hi/oa_pilot/h2020-hi-oa-pilot-guide_en.pdf
DEFINITION
•  Spannungsfeld: Anspruch – Wirklichkeit
•  „Research Data Infrastructures can be defined as managed
networked environments for digital research data consisting
of services and tools that support: (i) the whole research
cycle, (ii) the movement of research data across scientific
disciplines, (iii) the creation of open linked data spaces by
connecting data sets from diverse disciplines, (iv) the
management of scientific workflows, (v) the interoperation
between research data and literature and (vi) an integrated
Science Policy Framework.“
GRDI2020. (2012). GRDI2020 Final Roadmap Report. Global Research Data Infrastructures: The Big Data Challenges. Retrieved from http://
www.grdi2020.eu/Repository/FileScaricati/e2b03611-e58f-4242-946a-5b21f17d2947.pdf
TYPOLOGIE
•  Disziplinäre Forschungsdaten-Repositorien
•  Institutionelle Forschungsdaten-Repositorien
•  Projektspezifische Forschungsdaten-
Repositorien
•  Multidisziplinäre Forschungsdaten-
Repositorien
•  Portale, die verteile Datensammlungen
zugänglich machen
Pampel, H. et al. (2012). re3data.org: Aufbau eines Verzeichnisses von Forschungsdaten-Repositorien. Ein
Werkstattbericht. In B. Mittermaier (Ed.), Vernetztes Wissen – Daten, Menschen, Systeme. WissKom 2012
(pp. 61–73). Jülich: Verlag des Forschungszentrums Jülich. Retrieved from http://hdl.handle.net/2128/4699
Pampel, H. et al. (2013). Making Research Data Repositories Visible: The re3data.org Registry. PLOS ONE,
8(11), e78080. doi:10.1371/journal.pone.0078080
HERAUSFORDERUNGEN
•  „The three main challenges in developing an
ecosystem of data repositories are (1) gaps in the
present data infrastructure and (2) connectivity
issues (between the workflow of researchers and the
institutional data infrastructure and between
institutional and national data infrastructures) and
(3) long-term financial basis.“
Van der Graaf, M., & Waaijers, L. (2011). A Surfboard for Riding the Wave. Towards a four country action
programme on research data. Retrieved from http://www.knowledge-exchange.info/Admin/Public/
DWSDownload.aspx?File=/Files/Filer/downloads/Primary+Research+Data/Surfboard+for+Riding+the+Wave/
KE_Surfboard_Riding_the_Wave_Screen.pdf
HERAUSFORDERUNGEN
•  „Research data infrastructures must provide some
network-enabled “support services” in order to
achieve the conditions needed to facilitate effective
collaboration among spatially and institutionally
separated communities of research.“ (GRDI2020,
2012)
GRDI2020. (2012). GRDI2020 Final Roadmap Report. Global Research Data Infrastructures: The Big
Data Challenges. Retrieved from http://www.grdi2020.eu/Repository/FileScaricati/e2b03611-
e58f-4242-946a-5b21f17d2947.pdf
AKZEPTANZ
•  u. a. Abhängig von:
•  „connectivity issues“ – Integration in den
wissenschaftlichen Arbeitsablauf
•  „support services“ – Unterstützung und
Mehrwert
BEISPIEL: DRYAD
BEISPIEL: DRYAD
BEISPIEL: PANGAEA
Pampel, H. (2013): PANGAEA und Elsevier kooperieren. Retrieved from http://wisspub.net/
2010/01/12/pangaea-elsevier/
BEISPIEL: PANGAEA
BEISPIEL: PANGAEA
BEISPIEL: GFZ
http://dx.doi.org/10.2312/GFZ.b103-14046
BEISPIEL: GFZ
http://dx.doi.org/10.2312/GFZ.b103-14046
BEISPIEL: INSPIRE / HEP DATA
Cranmer, K. (2013): Enabling data sharing, citation, and discovery. Retrieved from http://
blog.inspirehep.net/2013/10/enabling-data-sharing-citation-and.html
BEISPIEL: INSPIRE / HEP DATA
INTELLIGENT OPENNESS
The Royal Society. (2012). Science as an open enterprise. The Royal Society Science Policy
Centre report 02/12. Retrieved from http://royalsociety.org/uploadedFiles/
Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf
Terms Definition
accessible „Data must be located in such a manner that it can readily be found
and in a form that can be used.“
assessable „In a state in which judgments can be made as to the data or
information’s reliability. Data must provide an account of the results of
scientific work that is intelligible to those wishing to under- stand or
scrutinise them. Data must therefore be differentiated for different
audiences.“
intelligible „Comprehensive for those who wish to scrutinise something.
Audiences need to be able to make some judgment or assessment of
what is communicated. They will need to judge the nature of the
claims made. They should be able to judge the competence and
reliability of those making the claims. Assessability also includes the
disclosure of attendant factors that might influence public trust.“
useable „In a format where others can use the data or information. Data
should be able to be reused, often for different purposes, and
therefore will require proper background information and meta- data.
The usability of data will also depend on those who wish to use them.“
INTELLIGENT OPENNESS
The Royal Society. (2012). Science as an open enterprise. The Royal Society Science Policy
Centre report 02/12. Retrieved from http://royalsociety.org/uploadedFiles/
Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf
Terms Definition
accessible „Data must be located in such a manner that it can readily be found
and in a form that can be used.“
assessable „In a state in which judgments can be made as to the data or
information’s reliability. Data must provide an account of the results of
scientific work that is intelligible to those wishing to under- stand or
scrutinise them. Data must therefore be differentiated for different
audiences.“
intelligible „Comprehensive for those who wish to scrutinise something.
Audiences need to be able to make some judgment or assessment of
what is communicated. They will need to judge the nature of the
claims made. They should be able to judge the competence and
reliability of those making the claims. Assessability also includes the
disclosure of attendant factors that might influence public trust.“
useable „In a format where others can use the data or information. Data
should be able to be reused, often for different purposes, and
therefore will require proper background information and meta- data.
The usability of data will also depend on those who wish to use them.“
HERAUSFORDERUNG
•  Beispiel: Biomedizin
Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape,
challenges and exemplars. ODIN first year conference. Retrieved from https://
indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
HERAUSFORDERUNG
•  Beispiel: Biomedizin
Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape,
challenges and exemplars. ODIN first year conference. Retrieved from https://
indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
HERAUSFORDERUNG
•  Beispiel: Biomedizin
Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape,
challenges and exemplars. ODIN first year conference. Retrieved from https://
indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
HERAUSFORDERUNG
•  Beispiel: Biomedizin
Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape,
challenges and exemplars. ODIN first year conference. Retrieved from https://
indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
VISION
Pampel, H. et al. (2014): Rolle und Perspektive von re3data.org bei der Förderung von Open
Science. 103. Deutscher Bibliothekartag, Bremen, 04.06.2014. Retrieved from: http://nbn-
resolving.de/urn:nbn:de:0290-opus-15741
RDA DEUTSCHLAND TREFFEN
•  Datum: 20. bis 21. November 2014
•  Ort: Deutsches GeoForschungsZentrum GFZ
•  Infos: http://tinyurl.com/RDAtreffen
10 PUNKTE
Pampel, H., Neumann, J., Fenner, M., & Tullney, M. (2014). Publikation
von Forschungsdaten. In Technischen Informationsbibliothek (TIB) (Ed.),
CoScience – Gemeinsam forschen und publizieren mit dem Netz. (Version
1). Hannover. doi:10.2314/coscv1.53
1.  Was erwarten Förderorganisationen?
2.  Welche Anforderungen haben
Journals?
3.  Wie organisiere ich meine Daten?
4.  Wie sichere ich meine Daten?
5.  Soll ich meine Daten veröffentlichen?
6.  Welche Vorteile hat das Data Sharing?
7.  Welche Nachteile hat das Data
Sharing?
8.  Wie finde ich ein Repositorium?
9.  Welchen Vorteil bieten Data Journals?
10. Wo finde ich weitere Informationen?
DANKE FÜR DIE
AUFMERKSAMKEIT!
•  Kontakt: pampel@gfz-potsdam.de
•  re3data.org: http://re3data.org
•  Wiki: http://forschungsdaten.org
•  Mailingliste: http://tinyurl.com/datenliste
•  GFZ / LIS: http://bib.telegrafenberg.de
Alle Texte dieser Präsentation, ausgenommen Zitate, sind
unter einem Creative Commons Namens-nennung 3.0
Deutschland Lizenzvertrag lizenziert. http://
creativecommons.org/licenses/by/3.0/de

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Tools für das Management von Forschungsdaten

  • 1. TOOLS FÜR DAS MANAGEMENT VON FORSCHUNGSDATEN Workshop „Wege in die Köpfe“ des DFG-Projekts „EWIG - Entwicklung von Workflowkomponenten für die Langzeitarchivierung von Forschungsdaten in den Geowissenschaften“ Berlin, 03.07.2014 Heinz Pampel, Deutsches GeoForschungsZentrum GFZ
  • 2. TOOLS – EINE AUSWAHL MATLAB R-Pakete GRASS GIS Tools zur Analyse von Forschungsdaten
  • 3. TOOLS – EINE AUSWAHL MATLAB R-Pakete GRASS GIS FileZilla Tools zur Analyse von Forschungsdaten Tools zum Austausch von „Daten“
  • 4. TOOLS – EINE AUSWAHL MATLAB R-Pakete GRASS GIS FileZilla LabArchives Tools zur Analyse von Forschungsdaten Tools zum Austausch von „Daten“ Tools zum Management von Forschungsdaten
  • 5. TOOLS – EINE AUSWAHL MATLAB R-Pakete GRASS GIS FileZilla LabArchives Tools zur Analyse von Forschungsdaten Tools zum Austausch von „Daten“ Tools zum Management von Forschungsdaten Tools zur dauerhaften Zugänglichkeit von Forschungsdaten
  • 6. TOOLS – EINE AUSWAHL Klump, J., & Bertelmann, R. (2013). D 8 Forschungsdaten. In R. Kuhlen, W. Semar, & D. Strauch (Eds.), Grundlagen der praktischen Information und Dokumentation. Berlin: De Gruyter Saur. doi:10.1515/9783110258264.575
  • 7. •  „Building a sound infrastructure for data sharing, preservation, and use is a challenge, but is in some ways easier than changing a culture.“ •  „The leading reasons were insufficient time and lack of funding.“ •  „These are difficult to solve, but systems that make it quick and easy to share data without cost may help.“ INFRASTRUKTUR ALS ANREIZ Tenopir, C. et al. (2011). Data Sharing by Scientists: Practices and Perceptions. PLoS ONE, 6(6), e21101. doi:10.1371/journal.pone.0021101
  • 8. INFRASTRUKTUR ALS ANREIZ •  „Building a sound infrastructure for data sharing, preservation, and use is a challenge, but is in some ways easier than changing a culture.“ •  „The leading reasons were insufficient time and lack of funding.“ •  „These are difficult to solve, but systems that make it quick and easy to share data without cost may help.“ Tenopir, C. et al. (2011). Data Sharing by Scientists: Practices and Perceptions. PLoS ONE, 6(6), e21101. doi:10.1371/journal.pone.0021101
  • 9. INFRASTRUKTUR ALS ANREIZ •  „A key finding is that incentives for data sharing have to be developed. These have to be linked to the academic incentive system as well as to the research assessment schemes.“ •  „The technical barriers to share data have to be reduced by simplifying data sharing workflows.“ •  „Several stakeholders, from publishers or data centres to funders have to be involved in this process to address researchers’ hesitation to manage their data and make them available.“ Dallmeier-Tiessen, S.; et al. (2012): D6.1 Summary of the Studies, Thematic Publications and Recommendations. Retrieved from doi.org/ 10.5281/zenodo.8305
  • 10. INFRASTRUKTUR ALS ANREIZ •  „A key finding is that incentives for data sharing have to be developed. These have to be linked to the academic incentive system as well as to the research assessment schemes.“ •  „The technical barriers to share data have to be reduced by simplifying data sharing workflows.“ •  „Several stakeholders, from publishers or data centres to funders have to be involved in this process to address researchers’ hesitation to manage their data and make them available.“ Dallmeier-Tiessen, S.; et al. (2012): D6.1 Summary of the Studies, Thematic Publications and Recommendations. Retrieved from doi.org/ 10.5281/zenodo.8305
  • 13. RAHMENBEDINGUNGEN •  Data Policies von Förderorganisationen •  Europäische Kommission: HORIZON 2020 Horizon 2020 Annotated Model Grant Agreements. Version 1.6. 2 May 2014. Retrieved from http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/amga/ h2020-amga_en.pdf
  • 14. RAHMENBEDINGUNGEN •  Data Policies von Förderorganisationen •  Europäische Kommission: HORIZON 2020 Spichtinger, D & Ramjoué, C. (2014): Open Access and the Open Research Data Pilot in H2020. EC Seminar. Retrieved from http://ec.europa.eu/information_society/ newsroom/cf/dae/document.cfm?action=display&doc_id=4602
  • 15. RAHMENBEDINGUNGEN •  Data Policies von Journals •  Beispiel PLOS ONE
  • 17. re3data.org •  Projektpartner: •  Deutsches GeoForschungsZentrum GFZ, Bibliothek und Informationsdienste (LIS) •  Humboldt-Universität zu Berlin, Institut für Bibliotheks- und Informationswissenschaft (IBI) •  Instituts für Technologie (KIT), KIT-Bibliothek •  Förderorganisation: •  Deutsche Forschungsgemeinschaft •  Phase 1: 2013-2014 •  Phase 2: 2014-2015 •  Diverse Kooperationspartner Pampel, H. et al. (2013). Making Research Data Repositories Visible: The re3data.org Registry. PLOS ONE, 8(11), e78080. doi:10.1371/journal.pone.0078080
  • 18. re3data.org •  Aufbau eines Verzeichnisses zur Beschreibung von Forschungsdaten-Repositorien •  Unterstützung für Forschende, Förderorganisationen und Einrichtungen der Informationsinfrastruktur •  Beitrag zur Weiterentwicklung der Forschungsdaten- Repositorien (Standardisierung und Professionalisierung) •  Nationaler Beitrag zur weltweiten Diskussion über die Schaffung von offenen Forschungsdaten-Infrastrukturen
  • 19. re3data.org •  Version 1.0 (2012) •  Resultat einer Bestandsaufnahme •  http://doi.org/10.2312/re3.001 •  Version 2.0 (2012) •  Ergebnis einer öffentlichen Konsultation •  http://doi.org/10.2312/re3.002 •  http://www.re3data.org/schema/2-0/ •  Version 2.1 (2013) •  Zusammenarbeit mit Kooperationspartnern •  http://doi.org/10.2312/re3.004 •  http://www.re3data.org/schema/2-1/ •  Neue Version in Arbeit (2014) Vierkant, P., et al. (2013). Schema for the Description of Research Data Repositories. Version 2.1. doi:10.2312/re3.004
  • 25. re3data.org •  Requirements •  be run by a legal entity, such as a sustainable institution (e.g. library, university) •  clarify access conditions to the data and repository as well as the terms of use •  have an English graphical user interface (GUI) •  have focus on research data Vierkant, P., et al. (2013). Schema for the Description of Research Data Repositories. Version 2.1. doi:10.2312/re3.004
  • 26. re3data.org Vierkant, P., et al. (2013). Schema for the Description of Research Data Repositories. Version 2.1. doi:10.2312/re3.004
  • 30. re3data.org •  Kooperationen: Förderorganisationen European Commisson. (2013). Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020. Retrieved from http://ec.europa.eu/ research/participants/data/ref/h2020/grants_manual/ hi/oa_pilot/h2020-hi-oa-pilot-guide_en.pdf
  • 31. DEFINITION •  Spannungsfeld: Anspruch – Wirklichkeit •  „Research Data Infrastructures can be defined as managed networked environments for digital research data consisting of services and tools that support: (i) the whole research cycle, (ii) the movement of research data across scientific disciplines, (iii) the creation of open linked data spaces by connecting data sets from diverse disciplines, (iv) the management of scientific workflows, (v) the interoperation between research data and literature and (vi) an integrated Science Policy Framework.“ GRDI2020. (2012). GRDI2020 Final Roadmap Report. Global Research Data Infrastructures: The Big Data Challenges. Retrieved from http:// www.grdi2020.eu/Repository/FileScaricati/e2b03611-e58f-4242-946a-5b21f17d2947.pdf
  • 32. TYPOLOGIE •  Disziplinäre Forschungsdaten-Repositorien •  Institutionelle Forschungsdaten-Repositorien •  Projektspezifische Forschungsdaten- Repositorien •  Multidisziplinäre Forschungsdaten- Repositorien •  Portale, die verteile Datensammlungen zugänglich machen Pampel, H. et al. (2012). re3data.org: Aufbau eines Verzeichnisses von Forschungsdaten-Repositorien. Ein Werkstattbericht. In B. Mittermaier (Ed.), Vernetztes Wissen – Daten, Menschen, Systeme. WissKom 2012 (pp. 61–73). Jülich: Verlag des Forschungszentrums Jülich. Retrieved from http://hdl.handle.net/2128/4699 Pampel, H. et al. (2013). Making Research Data Repositories Visible: The re3data.org Registry. PLOS ONE, 8(11), e78080. doi:10.1371/journal.pone.0078080
  • 33. HERAUSFORDERUNGEN •  „The three main challenges in developing an ecosystem of data repositories are (1) gaps in the present data infrastructure and (2) connectivity issues (between the workflow of researchers and the institutional data infrastructure and between institutional and national data infrastructures) and (3) long-term financial basis.“ Van der Graaf, M., & Waaijers, L. (2011). A Surfboard for Riding the Wave. Towards a four country action programme on research data. Retrieved from http://www.knowledge-exchange.info/Admin/Public/ DWSDownload.aspx?File=/Files/Filer/downloads/Primary+Research+Data/Surfboard+for+Riding+the+Wave/ KE_Surfboard_Riding_the_Wave_Screen.pdf
  • 34. HERAUSFORDERUNGEN •  „Research data infrastructures must provide some network-enabled “support services” in order to achieve the conditions needed to facilitate effective collaboration among spatially and institutionally separated communities of research.“ (GRDI2020, 2012) GRDI2020. (2012). GRDI2020 Final Roadmap Report. Global Research Data Infrastructures: The Big Data Challenges. Retrieved from http://www.grdi2020.eu/Repository/FileScaricati/e2b03611- e58f-4242-946a-5b21f17d2947.pdf
  • 35. AKZEPTANZ •  u. a. Abhängig von: •  „connectivity issues“ – Integration in den wissenschaftlichen Arbeitsablauf •  „support services“ – Unterstützung und Mehrwert
  • 38. BEISPIEL: PANGAEA Pampel, H. (2013): PANGAEA und Elsevier kooperieren. Retrieved from http://wisspub.net/ 2010/01/12/pangaea-elsevier/
  • 43. BEISPIEL: INSPIRE / HEP DATA Cranmer, K. (2013): Enabling data sharing, citation, and discovery. Retrieved from http:// blog.inspirehep.net/2013/10/enabling-data-sharing-citation-and.html
  • 45. INTELLIGENT OPENNESS The Royal Society. (2012). Science as an open enterprise. The Royal Society Science Policy Centre report 02/12. Retrieved from http://royalsociety.org/uploadedFiles/ Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf Terms Definition accessible „Data must be located in such a manner that it can readily be found and in a form that can be used.“ assessable „In a state in which judgments can be made as to the data or information’s reliability. Data must provide an account of the results of scientific work that is intelligible to those wishing to under- stand or scrutinise them. Data must therefore be differentiated for different audiences.“ intelligible „Comprehensive for those who wish to scrutinise something. Audiences need to be able to make some judgment or assessment of what is communicated. They will need to judge the nature of the claims made. They should be able to judge the competence and reliability of those making the claims. Assessability also includes the disclosure of attendant factors that might influence public trust.“ useable „In a format where others can use the data or information. Data should be able to be reused, often for different purposes, and therefore will require proper background information and meta- data. The usability of data will also depend on those who wish to use them.“
  • 46. INTELLIGENT OPENNESS The Royal Society. (2012). Science as an open enterprise. The Royal Society Science Policy Centre report 02/12. Retrieved from http://royalsociety.org/uploadedFiles/ Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf Terms Definition accessible „Data must be located in such a manner that it can readily be found and in a form that can be used.“ assessable „In a state in which judgments can be made as to the data or information’s reliability. Data must provide an account of the results of scientific work that is intelligible to those wishing to under- stand or scrutinise them. Data must therefore be differentiated for different audiences.“ intelligible „Comprehensive for those who wish to scrutinise something. Audiences need to be able to make some judgment or assessment of what is communicated. They will need to judge the nature of the claims made. They should be able to judge the competence and reliability of those making the claims. Assessability also includes the disclosure of attendant factors that might influence public trust.“ useable „In a format where others can use the data or information. Data should be able to be reused, often for different purposes, and therefore will require proper background information and meta- data. The usability of data will also depend on those who wish to use them.“
  • 47. HERAUSFORDERUNG •  Beispiel: Biomedizin Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape, challenges and exemplars. ODIN first year conference. Retrieved from https:// indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
  • 48. HERAUSFORDERUNG •  Beispiel: Biomedizin Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape, challenges and exemplars. ODIN first year conference. Retrieved from https:// indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
  • 49. HERAUSFORDERUNG •  Beispiel: Biomedizin Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape, challenges and exemplars. ODIN first year conference. Retrieved from https:// indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
  • 50. HERAUSFORDERUNG •  Beispiel: Biomedizin Sansone, S. A, (2013). Data standards, sharing and publication in life sciences: landscape, challenges and exemplars. ODIN first year conference. Retrieved from https:// indico.cern.ch/conferenceOtherViews.py?view=standard&confId=238868
  • 51. VISION Pampel, H. et al. (2014): Rolle und Perspektive von re3data.org bei der Förderung von Open Science. 103. Deutscher Bibliothekartag, Bremen, 04.06.2014. Retrieved from: http://nbn- resolving.de/urn:nbn:de:0290-opus-15741
  • 52. RDA DEUTSCHLAND TREFFEN •  Datum: 20. bis 21. November 2014 •  Ort: Deutsches GeoForschungsZentrum GFZ •  Infos: http://tinyurl.com/RDAtreffen
  • 53. 10 PUNKTE Pampel, H., Neumann, J., Fenner, M., & Tullney, M. (2014). Publikation von Forschungsdaten. In Technischen Informationsbibliothek (TIB) (Ed.), CoScience – Gemeinsam forschen und publizieren mit dem Netz. (Version 1). Hannover. doi:10.2314/coscv1.53 1.  Was erwarten Förderorganisationen? 2.  Welche Anforderungen haben Journals? 3.  Wie organisiere ich meine Daten? 4.  Wie sichere ich meine Daten? 5.  Soll ich meine Daten veröffentlichen? 6.  Welche Vorteile hat das Data Sharing? 7.  Welche Nachteile hat das Data Sharing? 8.  Wie finde ich ein Repositorium? 9.  Welchen Vorteil bieten Data Journals? 10. Wo finde ich weitere Informationen?
  • 54. DANKE FÜR DIE AUFMERKSAMKEIT! •  Kontakt: pampel@gfz-potsdam.de •  re3data.org: http://re3data.org •  Wiki: http://forschungsdaten.org •  Mailingliste: http://tinyurl.com/datenliste •  GFZ / LIS: http://bib.telegrafenberg.de Alle Texte dieser Präsentation, ausgenommen Zitate, sind unter einem Creative Commons Namens-nennung 3.0 Deutschland Lizenzvertrag lizenziert. http:// creativecommons.org/licenses/by/3.0/de