Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.



Published on

Published in: Education
  • Want to preview some of our plans? You can get 50 Woodworking Plans and a 440-Page "The Art of Woodworking" Book... Absolutely FREE ★★★
    Are you sure you want to  Yes  No
    Your message goes here
  • Be the first to like this


  1. 1. Publication of Research DataPublication of Research Data Marianne van der HeijdenMarianne van der Heijden November 3, 2010November 3, 2010
  2. 2. ► dddfdddf ““Scientists need to ensure thatScientists need to ensure that their results will be managedtheir results will be managed for the long haul.for the long haul. Maintaining dataMaintaining data takes bigtakes big organization”.organization”. Clifford Lynch,Clifford Lynch, NatureNature Special on Big DataSpecial on Big Data (3 Sept. 2008)(3 Sept. 2008)
  3. 3. Stelling 1:Stelling 1: Voornaamste problemen rondomVoornaamste problemen rondom data publicatie zijn technischedata publicatie zijn technische aspectenaspecten
  4. 4. Stelling 2:Stelling 2: Data management is ‘commonData management is ‘common practice’ bij onderzoeksinstitutenpractice’ bij onderzoeksinstituten
  5. 5. Stelling 3:Stelling 3: Alle belangrijke onderzoeksdataAlle belangrijke onderzoeksdata wordt in artikelen gepubliceerd.wordt in artikelen gepubliceerd. Het apart publiceren van data isHet apart publiceren van data is dan ook overbodig.dan ook overbodig.
  6. 6. Who are involved?Who are involved? ► FundersFunders ► Researchers as dataResearchers as data producersproducers ► Data archivesData archives ► JournalsJournals ► Researchers as dataResearchers as data consumersconsumers
  7. 7. Building a frameworkBuilding a framework ► Together with researchersTogether with researchers ► Appoint contact persons per departmentAppoint contact persons per department ► Hosting(outsourcing) & support of the ICTHosting(outsourcing) & support of the ICT environmentenvironment ► Discovery and archiving systemDiscovery and archiving system
  8. 8. Research dataResearch data ► long term access/availability (repository)long term access/availability (repository) ► usable data formatusable data format ► Reliable / Peer review / QualityReliable / Peer review / Quality ► MetadataMetadata
  9. 9. TechniqueTechnique Trusted RepositoryTrusted Repository Data Seal of ApprovalData Seal of Approval
  10. 10. MetadataMetadata ► descriptive metadatadescriptive metadata  to find, cite and understand datato find, cite and understand data ► structural metadatastructural metadata  how to process the data and the relationshow to process the data and the relations between filesbetween files ► administrative metadataadministrative metadata  intellectual property, conditions for use andintellectual property, conditions for use and accessaccess
  11. 11. Step-by-Step ApproachStep-by-Step Approach ► Inventarisation of dataInventarisation of data ► Structuring of the data filesStructuring of the data files  Training and checklists to start as early as possible withTraining and checklists to start as early as possible with structured datastructured data ► Creation of datasetsCreation of datasets  Uniformity of filesUniformity of files ► Archiving of the data setsArchiving of the data sets ► Publishing of the metadata for discoveryPublishing of the metadata for discovery
  12. 12. Motivation and AwarenessMotivation and Awareness ► Benefits of data archiving ► Recognition from data publishing ► Demands from publishers and financiers ► NIOODATA wiki ► Data day as a joint data archiving exercise
  13. 13. Benefits of Data PublicationBenefits of Data Publication ► Enhance the visibility of your workEnhance the visibility of your work ► Avoid data loss and corruptionAvoid data loss and corruption  Work more efficientlyWork more efficiently ► Facilitate Data ExchangeFacilitate Data Exchange ► Moral obligationMoral obligation  Costs of data collection (instruments, equipment,workforce)Costs of data collection (instruments, equipment,workforce)  Uniqeness of field observations (You cannot measure a value fromUniqeness of field observations (You cannot measure a value from 2003 in 2010 )2003 in 2010 ) ► Obtain scientific recognition for your work:Obtain scientific recognition for your work:  Publishing a data paper (Example Ecological Archives)Publishing a data paper (Example Ecological Archives)  Make your dataset ‘citable’ (datacentrum 3TU gives DOI)Make your dataset ‘citable’ (datacentrum 3TU gives DOI)  Data citation from NIOO Data PortalData citation from NIOO Data Portal
  14. 14. DataData RepositoryRepository DANSDANS 3 TUD3 TUD
  15. 15. Other RepositoriesOther Repositories ► DistributedDistributed  IPY DataIPY Data ► InstitutionalInstitutional  NIOO / VLIZNIOO / VLIZ
  16. 16. Data Management Process:
  17. 17. Results pilot studyResults pilot study ► 21.393 files, 3.421 archived in 91 datasets21.393 files, 3.421 archived in 91 datasets ► Some files integratedSome files integrated ► Idea buildingIdea building  Procedures and agreementsProcedures and agreements  Different formats request different systemsDifferent formats request different systems  Data “rescue” actionData “rescue” action  Integration necessityIntegration necessity
  18. 18. VLIZ takes care for NIOOVLIZ takes care for NIOO ► Guidelines and procedures for DataGuidelines and procedures for Data Management and Data StoringManagement and Data Storing ► Two 3-day workshopsTwo 3-day workshops ► Data “rescue” actionData “rescue” action ► Help with archivingHelp with archiving ► Elaborate formatsElaborate formats ► Enhance GuidelinesEnhance Guidelines  in cooperation with researchersin cooperation with researchers
  19. 19. UserfriendlinessUserfriendliness ► Integration of archiving with workflow stepsIntegration of archiving with workflow steps ► Selection criteriaSelection criteria ► Interface Design with default suggestionsInterface Design with default suggestions  example Morphoexample Morpho
  20. 20. Morpho: datamanagement for ecologistsMorpho: datamanagement for ecologists
  21. 21. Data Management PlanData Management Plan ► Start working timely and efficiently with data managementStart working timely and efficiently with data management  In US+ UK stellen sommige financiers dit al verplichtIn US+ UK stellen sommige financiers dit al verplicht
  22. 22. Data life cycleData life cycle
  23. 23. Data PublicationData Publication ► IOCD workshop on DataIOCD workshop on Data PublishingPublishing ► Ecological ArchivesEcological Archives
  24. 24. Data citationData citation 3 TU – DOI3 TU – DOI NIOO datacitationNIOO datacitation
  25. 25. Digital PreservationDigital Preservation
  26. 26. Take home thoughts ► Technology is facilitating, not prescribing ► Motivation is essential ► Resolutions in close contact with researcher ► Start as early as possible in data life cycle process ► Start up rather expensive in investing in infrastructure and in coaching people
  27. 27. Cooperate !Cooperate !
  28. 28. ThanksThanks ► Links to resources:Links to resources: ► ► Links to presentation:Links to presentation: ►
  29. 29. Delicious ► Data Archiving and Networked Services | Over DANS ► Data en information management NIOO ALGBAC, voorbeeld data citatie ► Digital Preservation Tutorial: Table of Contents ► DMP ► DMP_checklist.pdf (application/pdf-object) ► Ecological Archives Preparing Data Papers Data publicatie ► Info | Data Seal of Approval ► International Polar Year Portal ► IODE Workshop on Data Publishing ► KNB Data :: Morpho Data management for ecologists ► Manage Your Data: Data Management: Subject Guides: MIT Libraries ► Open Data Commons » Blog Archive » Draft of an Open Data Commons Attribution License ► Panton Principles ► VLIZ : VMDC Nieuws ► Wordle - Create