1. Data organisation & description Library – RDM Support Project Basic training course for information specialists

2. RDMS Data organisation & description2 Reasons for organisation & description  Human memory is fallible  All employment contracts come to an end sometime  Explaining the same thing over and over again gets boring

3. RDMS Data organisation & description3 Aim of organisation & description Ensuring that the origin, structure and content of a dataset are comprehensible to everyone at all times

4. RDMS Data organisation & description4 Test question What does someone who is not familiar with your data need in order to find, assess, understand and reuse your data?

5. RDMS Data organisation & description5 Temperature: 32.3 Measured? Calculated? How? When? Where? Temperature of what? Unit? Fahrenheit? Celsius? Measured with what? Was the equipment calibrated, and if so how?

6. Organisation RDMS Data organisation & description6

7. 7 Benefit of organisation  Finding files easily (saving time)  Separating ongoing and completed work (maintaining an overview)  Separating master files and working files (preventing loss of files)

8. RDMS Data organisation & description8 Do's  Assign clear names to folders and subfolders  Limit the number of levels in hierarchy  Describe structure in a readme.txt

9. RDMS Data organisation & description9 Don’ts  Name folders and subfolders after researchers  Make identification of files dependent on the folder that contains them  Have organisation determined by software from which file structure cannot be exported

10. File names RDMS Data organisation & description10 Piled Higher and Deeper by Jorge Cham http://www.phdcomics.com/comics/archive.php?comicid=1531 http://www.phdcomics.com/comics/archive.php?comicid=1531

11. RDMS Data organisation & description11 Good file names  make files findable  help to distinguish between different files and versions of files  prevent confusion when sharing files

12. RDMS Data organisation & description12 Possible building blocks  Brief description of content  Maker or indication of measuring instrument  Creation, recording or publication date  Version number  Project number and/or name of the research group

13. RDMS Data organisation & description13 Practical tips  Make file names relevant and short (approx. 25 characters)  Do not use any special characters in file name  Use _underscores_ instead of spaces

14. RDMS Data organisation & description14 Practical tips  Always enter dates in file names in the same way (yyyymmdd / yymmdd)  Abbreviations or initials in the file name? Enter the meaning in a readme.txt

15. Version management  Successive versions? Use numbers (v01, v02, etc.) instead of designations such as "draft" or "final"  Different versions of the same file? Indicate this in the file name (e.g. ‘tb’ for thumbnail)  If applicable: software for version management (SVN) RDMS Data organisation & description15

16. RDMS Data organisation & description16 Test question Does the file name contain the information needed to identify the file, regardless of where the file is stored?

17. RDMS Data organisation & description17 Example../Research Data Management/Second outline for the course January 2014.docx better:../201401_RDMCourseOutline_v02.docx../201401RDMCourseOutline02.docx

18. RDMS Data organisation & description18 Renaming files  Bulk Rename Utility (Windows) Bulk Rename Utility  Renamer 4 Mac (Mac) Renamer 4 Mac  Renamer (Mac) Renamer  PS Renamer (Windows, Mac, Linux) PS Renamer

19. Metadata RDMS Data organisation & description19 Dan Cohen is Executive Director of the Digital Public Library of America (DPLA) https://twitter.com/dancohen/status/431440078951682049

20. Metadata: functions RDMS Data organisation & description20  Make datasets findable: metadata provide the building blocks that a repository's search function needs  Make datasets citable: metadata provide the elements for a citation of a dataset

21. RDMS Data organisation & description21 Types of metadata  Descriptive: identification, location, classification  Technical: file formats, equipment settings, software or hardware used  Administrative: property rights, licence  Use: access rights, embargo  Retention: checksums, migration, conversion

22. RDMS Data organisation & description22 When to use metadata?  Generally assigned when sharing, publishing and/or filing data  Embedded metadata: automatically saved in file (≠ guarantee when moving file)

23. RDMS Data organisation & description23 http://www.flickr.com/photos/surfannemiek/3038325213/

24. RDMS Data organisation & description24 http://www.flickr.com/photos/surfannemiek/3038325213/meta

25. RDMS Data organisation & description25

26. RDMS Data organisation & description26 Standards  Generic: Dublin Core, DataCite  Field-specific: e.g. Data Documentation Initiative (DDI, Social Sciences)  Standards of repositories and data portals Searchable overview on DCC websiteDCC website

27. Dublin Core® Metadata Initiative (DCMI) Contributor Coverage Creator Date Description Format Identifier Language Publisher Relation Rights Source Subject Title Type RDMS Data organisation & description27

28. RDMS Data organisation & description28 Example taken from https://library.uoregon.edu/datamanagement/metadata.htmlhttps://library.uoregon.edu/datamanagement/metadata.html

29. Search function RDMS Data organisation & description29

30. DataCite properties AlternateIdentifier (O) Contributor (R) Creator (M) Date (R) Description (R) Format (O) GeoLocation (R) Identifier (M) Language (O) PublicationYear (M) Publisher (M) RelateIdentifier (R) ResourceType (R) Rights (O) Size (O) Subject (R) Title (M) Version (O) RDMS Data organisation & description30 M = mandatory, R = recommended, O = optional

31. DataCite properties RDMS Data organisation & description31 More examples at http://schema.datacite.org/meta/kernel-3/index.htmlhttp://schema.datacite.org/meta/kernel-3/index.html

32. Choosing a standard RDMS Data organisation & description32  Which type of data is the researcher collecting?  What is customary in the field or research group?  Where is the data going to be deposited (= what does the repository want and what can it do)?

33. Challenge RDMS Data organisation & description33 Convert the information a researcher has on his or her dataset into the metadata fields used in a repository Often far more multiple fields are possible and desired by the researcher beforehand than are actually entered and used when searching (= experience from previous data storage project)

34. Metadata: tools RDMS Data organisation & description34 http://library.stanford.edu/research/data-management-services/data-best- practices/creating-metadata/metadata-tools-comparison

35. Documentation RDMS Data organisation & description35

36. RDMS Data organisation & description36 (Meta)data vs documentation  Data  Metadata: description of data for computers  Documentation: description of data for humans

37. RDMS Data organisation & description37 (Meta)data vs documentation - example  Dataanswers to questions  Metadatamaker of survey, date survey taken, etc.  Documentationsurvey itself, description of method used, etc.

38. RDMS Data organisation & description38 Documentation at three levels  Research project: context, methodology, instruments  Dataset or database: relationship between files  File: content and structure of individual files (variables, codes, etc.)

39. RDMS Data organisation & description39 Test question What does someone who is not familiar with your data need in order to assess, understand and reuse your data?

40. In practice… RDMS Data organisation & description40 Edinburgh University Data Library [Data Library]. (2012, May 4). MANTRA – John MacInnes – Data documentation in secondary data analysis. Retrieved from http://youtu.be/Ebaiwg08CW8 http://youtu.be/Ebaiwg08CW8

41. RDMS Data organisation & description41 Information sources Digital Curation Centre (DCC), Resources for digital curators: Disciplinary Metadata http://www.dcc.ac.uk/resources/metadata-standards Dublin Core® Metadata Initiative User Guide http://wiki.dublincore.org/index.php/User_Guide DataCite Metadata Schema http://schema.datacite.org/meta/kernel-3/index.html Stanford University Libraries, Metadata tools http://library.stanford.edu/research/data-management-services/data-best-practices/creating- metadata/metadata-tools

42. RDMS Data organisation & description42 Publication information Presentation: Mariëtte van Selm | selm@uva.nlselm@uva.nl Images, unless credited otherwise: Jørgen Stamp | http://www.digitalbevaring.dk/http://www.digitalbevaring.dk/ M. van Selm, RDM Support - basic training course for information specialists, course material for session 4. February 2014. This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International licenceCreative Commons Attribution-ShareAlike 4.0 International