A checklist and introduction to the Data Curation Network CURATE Steps for curating research data

Carlson, Jake R.

Hudson-Vitale, Cynthia

Imker, Heidi

Johnston, Lisa

Kozlowski, Wendy

Olendorf, Robert

English

Washington University St. Louis: Open Scholarship

Washington University in St. LouisWashington University Open ScholarshipIASSIST & DCN - Data Curation Workshop Workshop ScheduleDec 11th, 10:40 AM - 11:00 AMChecklist of DCN CURATE StepsLisa JohnstonUniversity of Minnesota - Twin Cities, ljohnsto@umn.eduJake R. CarlsonUniversity of Michigan - Ann Arbor, jakecar@umich.eduWendy KozlowskiCornell University Library, wak57@cornell.eduHeidi ImkerUniversity of Illinois at Urbana-Champaign, imker@illinois.eduRobert OlendorfThe Pennsylvania State University, rko5039@psu.eduSee next page for additional authorsFollow this and additional works at: https://openscholarship.wustl.edu/data-curation-workshop-2017Part of the Library and Information Science CommonsThis Handout is brought to you for free and open access by the Conferences and Symposia at Washington University Open Scholarship. It has beenaccepted for inclusion in IASSIST & DCN - Data Curation Workshop by an authorized administrator of Washington University Open Scholarship. Formore information, please contact digital@wumail.wustl.edu.Johnston, Lisa; Carlson, Jake R.; Kozlowski, Wendy; Imker, Heidi; Olendorf, Robert; and Hudson-Vitale, Cynthia, "Checklist of DCNCURATE Steps" (2017). IASSIST & DCN - Data Curation Workshop. 4.https://openscholarship.wustl.edu/data-curation-workshop-2017/schedule/Schedule/4Presenter InformationLisa Johnston, Jake R. Carlson, Wendy Kozlowski, Heidi Imker, Robert Olendorf, and Cynthia Hudson-VitaleThis handout is available at Washington University Open Scholarship: https://openscholarship.wustl.edu/data-curation-workshop-2017/schedule/Schedule/4IASSIST-Data Curation Network (DCN) Training Handout and Notes Checklist of CURATE Steps and FAIRness Scorecard (published in the ​DCN Planning Phase Report (2017​)  Check ​files and read documentation ​(risk mitigation, file inventory, appraisal/selection) Understand ​the data (or try to), if not… ​(run files/environment, QA/QC issues, readmes) Request ​missing information or changes ​(tracking provenance of any changes and why) Augment ​metadata for findability (​DOIs, metadata standards, discoverability) Transform ​file formats for reuse ​(data preservation, conversion tools, data viz) Evaluate ​for FAIRness ​(licences, responsibility standards, metrics for tracking use)  Notes     1 IASSIST-Data Curation Network (DCN) Training Handout and Notes CHECK Step CURATE Action Curator Checklist Check​ data files and read documentation ● Review the content of the data files (e.g., open and run the files or code). ● Verify all metadata provided by the author and review the available documentation.  ❏ Files open as expected ❏ Issues __________  ❏ Code runs as expected  ❏ Produces minor errors  ❏ Does not run and/or produces many errors ❏ Metadata quality is rich, accurate, and complete ❏ Metadata has issues _________ ❏ Documentation Type (circle) Readme / Codebook / Data Dictionary / Other: ________________________ ❏ Missing/None ❏ Needs work   Notes:    2 IASSIST-Data Curation Network (DCN) Training Handout and Notes UNDERSTAND Step  CURATE Action Curator Checklist Understand​ the data (or try to) ● Check for quality assurance and usability issues such as missing data, ambiguous headings, code execution failures, and data presentation concerns.  ● Try to detect and extract any “hidden documentation” inherent to the data files that may facilitate reuse.  ● Determine if the documentation of the data is sufficient for a user with similar qualifications to the author’s to understand and reuse the data. If not, recommend or create additional documentation (e.g., a readme.txt template). Varies based on file formats and subject domain. For example….  Tabular Data Questions (Microsoft Excel) ❏ Organization of data well-structured ❏ Not rectangular  ❏ Split tables into separate tabs ❏ Headers/codes clearly defined ❏ Define headers ❏ Clarify codes used ________ ❏ Clarify use of “blanks” ❏ Clarify units of measurement ❏ Quality control clearly defined ❏ Unclear quality control ❏ Update/add Methodology   Notes:    3 IASSIST-Data Curation Network (DCN) Training Handout and Notes REQUEST Step  CURATE Action Curator Checklist Request​ missing information or changes  ● Generate a list of questions for the data author to fix any errors or issues. Narrative describing the concerns, issues, and needed improvements to the data submission.  University of Michigan sample email to researcher: Dear [name of the person Identified as the contact for the data set as stated in the DBD metadata],   Thank you for depositing your data set, [title of the data set] to the library’s Deep Blue Data repository.   After we receive a data set, we review it to ensure that the data sets we host are as complete, accessible and understandable as possible.  We have reviewed your data set and have the following recommendations for you:   ● Recommendation #1 ● Recommendation #2 ● Recommendation #3 ● Recommendation #4   We look forward to hearing your response to our questions and requests for additional information.  Please do let us know if you have any questions about or recommendations. We would be happy to talk with you over the phone or meet with you in person to discuss our review of your data should you wish to do so.  Sincerely,   [Name of Liaison]   Notes:     4 IASSIST-Data Curation Network (DCN) Training Handout and Notes AUGMENT Step  CURATE Action Curator Checklist Augment​ the submission  ● Enhance metadata to best facilitate discoverability. ● Create and apply metadata for the data record, including descriptive keywords. ● When appropriate, structure and present metadata in domain-specific schemas to facilitate interoperability with other systems. ❏ Discoverability sufficient ❏ Recommend (circle one) full-text index / file rename / file reorder / file descriptions / zip files into one archive Other  ______________ ❏ Keywords Sufficient ❏ Suggestions _______________ ❏ Linkages Sufficient ❏ Link to report/paper ❏ Link to related data sets ❏ Link to source data ❏ Link to other ____________  Notes:    5 IASSIST-Data Curation Network (DCN) Training Handout and Notes TRANSFORM Step  CURATE Action Curator Checklist Transform​ file formats ● Identify specialized file formats and their restrictions (e.g., Is the software freely available? Link to it or archive it alongside the data).  ● Transform files into open, non-proprietary file formats that broaden the potential audience for reuse and ensure that preservation actions might be taken by the repository in later steps. Retain original files if data transfer is not perfect. ❏ Preferred file formats in use ❏ Recommend conversion  from _________  to     _________ ❏ Retain original formats ❏ Software needed is readily available ❏ Unclear version of software ❏ Unclear software used  ❏ Visualization of data easily accessible ❏ Recommend graphical representation ____________ ❏ Recommend web-accessible surrogate ________________  Cornell’s List of Preservation Format Recommendations http://guides.library.cornell.edu/ecommons/formats   Notes:    6 IASSIST-Data Curation Network (DCN) Training Handout and Notes EVALUATE Step  CURATE Action Curator Checklist Evaluate​ and rate the overall data record for FAIRness.* ● Score the dataset and recommend ways to increase the FAIRness of the data and become “DCN approved.” Findable -  ❏ Metadata exceeds author/ title/ date,  ❏ Unique PID (DOI, Handle, PURL, etc.).  ❏ Discoverable via web search engines. Accessible -  ❏ Retrievable via a standard protocol (e.g., HTTP).  ❏ Free, open (e.g., download link).  Interoperable -  ❏ Metadata formatted in a standard schema (e.g., Dublin Core).  ❏ Metadata provided in machine-readable format (OAI feed). Reusable -  ❏ Data include sufficient metadata about the data characteristics to reuse  ❏ Contact info displayed if the direct assistance of the author needed. ❏ Clear indicators of who created, owns, and stewards the data. ❏ Data are released with clear data usage terms (e.g., a CC License). *  Rubric evaluating the FAIR principles are based on the scoring matrix by Dunning, de Smaele, & Böhmer (2017).   Notes: 7 

Checklist of DCN CURATE Steps

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Checklist of DCN CURATE Steps

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