DATA MANAGEMENT PLANS

Transcription

1 DATA MANAGEMENT PLANS DeeAnn Allison 317 Love Library (402) Leslie Delserone 210 C.Y. Thompson Library (402)

2 Required by many federal funding agencies Required for responsible research, including reproducibility. Establishes provenance for original research data Starts before project initiation and is followed through the life of the project During or upon project completion, data are stored (preserved) for : Retrieval and re-use by the researcher or others Sharing with a broader community (based on the funder s requirements and the researcher s data management plan) What is going to be collected? DATA MANAGEMENT - WHY? What are the formats? How will data be stored and protected? What will be shared? What will I do when the project is complete?

3 A recent retraction notice for a 2007 paper in the Journal of Clinical Investigation: It has come to our attention that some of the panels in Figure 5 appear to be duplications of each other. The authors are unable to provide the original source files that were used to generate these data. In the absence of the original data that verify the integrity of the images, the JCI Editorial Board has decided to withdraw Figure 5 from the scientific record. No issues have been raised in regard to any of the other data in this manuscript. The authors concur with this course of action. Source: DATA MANAGEMENT MATTERS

4 Many federal funders require data management plans - you don t want your grant proposal refused because you didn t do an adequate job. Check the funding agency s requirements more than once during your proposal preparation because their requirements are changing DATA MANAGEMENT IS A MOVING TARGET

5 Data management plans typically focus on the data management process: Data content and format Data collection, documentation and storage Data security and sharing ( rights ) Data retention and preservation; includes task assignments for data life cycle The disciplinary field and nature of the study will influence these decisions WHAT IS A DATA MANAGEMENT PLAN?

6 Data exist in a variety of formats Ideally a format should be nonproprietary Consider data normalization so data can be interpreted correctly File compression can be useful but you must understand the consequences De-identifying data is critical FILE FORMATS AND TRANSFORMATIONS

7 Select a format that will be most usable for the life cycle of the project The PRONOM registry ( is a useful site about formats Domain registries also have requirements about file formats for deposits Librarians can also answer questions and make suggestions FORMATS A file format is a way of encoding information within a digital file. A program or application must recognize the file format in order to access the file.

8 Considerations for format selection(s): Verify that the technical specification for the formats is available Use a well-established format that is in wide use Select a stable format that isn t under going rapid change Formats that support metadata are a plus because they can provide provenance and technical characteristics Avoid formats with built-in features and functionality that can become obsolete and/or lose functionality when they are migrated Select formats with error detection to keep your data from becoming corrupt (e.g., PNG uses byte sequences to check for errors) Text files can be human readable and use a character encoding standard, while binary files can only be read by software that handle that format

9 Potential risks for loss or corruption on conversion or migration to new media: o Word files fonts, text formatting, headers, footers, footnotes, links to other documents, any embedded functionality o Numeric files special characters (such as quotation marks), end of line returns, last characters in rows (due to row size limitations), last rows (due to row number limitations), formulae o Database files as above, but also relationships between tables o Multimedia files artifacts or distortion, loss of layers, color, resolution, and changes in codecs o File sizes may change and even become much larger FORMAT CHALLENGES

10 Some TIPS Agree on scale and other characteristics that support comparisons and interpretation Non-numeric qualitative data should be converted to numbered (quantitative) data that is standardized. This is called statistical normalization (where a formula is used to transform values into numbers that can be better compared) Database normalization is a set of design rules that eliminate duplication and inconsistency Interoperability requires normalized data Normalized data conform to common characteristics allowing for easy re-use by different users and/or the data to be understood by different applications NORMALIZATION

11 Saves space on storage devices and reduces transmission time when files are transferred over networks Some issues with compression Compressed files are subject to corruption and are more difficult to recover Some files don t save much space when compressed (multimedia files), while text files can save much space (up to 90%) Avoid lossy file compression types. Tiff images are lossless so you can make copies from them without losing quality Compressed files can take a long time to decompress so best for files that are no longer in active use FILE COMPRESSION

12 DATA CONTENT, FORMAT, & STORAGE IN A PLAN Type of Data Physical specimens Description of Data Soil samples Morphologically-analyzed specimens, stored for future PCR amplifications Voucher specimens: Individual specimen, fixed on glass microscope slide Individual specimen, stored in formalin Measurements of specimens Digital images Nucleotide sequences Sequence alignments, trees Range of characteristics measured; presence/absence of structures noted. Stored in Excel spreadsheets (flat file) for later export as.csv into Specify6 database Photomicrographs of each specimen, and scanning electron images of selected specimens, in JPG and TIFF formats FileMaker Pro v.7 files containing unique specimen identified and amplified sequence data using three primer sets FASTA files for submissions to GenBank

13 Privacy individual is known/identified Privacy concern what data may be collected and/or shared about this individual? Confidentiality identity of individual is not to be disclosed Confidentiality concern are there data that identify, or could be used to identify, a research participant? PRIVACY & CONFIDENTIALITY

14 Anonymization is the removal of any identifiers, such as name and address, that could be used to link data with an individual Replace sensitive information with machine generated codes Aggregate the data into related categories to provide analysis at a higher level than the level of the data collection. Census data are often aggregated Perturbation: Techniques for the release of data that change the data before the dissemination in such a way that the disclosure risk for the confidential data is decreased but the information content is retained as far as possible. (source: DE-IDENTIFICATION OF DATA

15 Documentation careful information-gathering on the who, what, where, when, and why of your research often an idiosyncratic, human-powered process Formats paper field or laboratory notebooks, digital photos DOCUMENTATION AND METADATA

16 Metadata data about data often standards-based describes the research data collection, but also captures other information (administrative, technical) generated manually &/or automatically DOCUMENTATION AND METADATA

17 METADATA IN A PLAN Type of Data Physical specimens Measurements of physical specimens Digital images Nucleotide sequences Sequence alignments, trees Description of Metadata We will utilize the Darwin Core metadata scheme. This standard is straightforward, sufficiently descriptive, and widely adopted by evolutionary biologists and ecologists. Each specimen is assigned a unique identifier. We will work with a metadata expert from UNL Libraries to create a template that captures each specimen s metadata and that conforms to the data submission requirements of relevant museums and repositories. Darwin Core metadata embedded in each JPG and TIFF file Unique identifier connects sequence to specimen s provenance metadata GenBank s required metadata for submission, including accession number

18 What are the relevant data and metadata standards in your area of research/discipline? How will you capture the metadata (manually, automatically, both)? How will you merge documentation with metadata? Do you have a data dictionary, controlled vocabulary, or code book that should be shared? APPLICATION TO YOUR RESEARCH

19 Professional societies, research journals University Libraries Data Curation Committee Librarian assigned to your department or program ( ) ASSISTANCE

20 Keeping data safe and secure is your responsibility Follow the policies and practices set-up by your college and the University Information Technology Services can assist with security planning Never accept or store Social Security Numbers ( Effective January 1, 2007, Social Security Numbers (SSNs) - including any portion of the full nine digits-shall not be electronically collected, transmitted, or stored via University-sponsored services or using University-owned computing equipment, information systems or networks unless specifically authorized in writing by officials designated by the Chancellor. Individuals or departments that collect, transmit or store SSNs will take steps necessary to secure this data using best practices identified by the Chief Information Officer. Failure to comply with this policy after January 1, 2007 may result in disciplinary actions taken by the University. STORAGE & SECURITY

21 Who will be responsible for securing sensitive data? Are there privacy issues? Are there data relating to human subjects? What are the policies/procedures/ethical requirements regarding these data? How will privacy &/or confidentiality requirements be enforced? By whom? QUESTIONS

22 Local control: Know where your data are located and who has access Never share passwords or leave them visible or accessible Know the number of copies (of files, notebooks, etc.) and where they are stored Safeguard all local copies (laptops, USB drives, notebooks, etc.) Sanitize drives you no longer need to ensure data is not recoverable Back-up your data KEYS TO DATA SECURITY

23 Network-level (and beyond) control: Use encryption and firewalls when appropriate Keep your virus protection up to date Take precautions when you send data via Ensure that remote access (off campus) connections are made securely using SSH or VPN ( Use a centrally managed server when possible Understand your rights when you deposit in a domain depository KEYS TO DATA SECURITY

24 Are any of the data copyrighted? Who holds copyright? Third-party ownership of the data? Licensing/repository policy on re-use of the data, its citation, production of derivatives? Any time-restrictions on access or use of the data? Metadata requirements to ensure accessibility? DATA RIGHTS AND ACCESS

25 Are the data subject to open-access requirements? FOIA requests? Expectations of the funders? Licensing (Creative Commons, Open Knowledge Foundation) Access through trusted repositories (e.g., DRYAD, ICPSR) DATA RIGHTS AND ACCESS

26 DATA SECURITY & SHARING IN A PLAN All digital data are stored on password-protected computers in the laboratory. These data are backed up weekly - manually on external hard drives by assigned laboratory technicians, and virtually by the University. Physical specimens are stored in secure coldrooms and secure laboratory spaces. All parties involved in this research are committed to the free and open sharing of scientific data produced during this research. The data are low-risk; we anticipate no sensitive or confidential data. Under the terms of the Open Data Commons Open Data License (ODbL 1.0; users may share, create, and/or adapt the data; we request attribution, sharing by users under the terms of the ODbL, and redistribution without digital restriction measures.

27 Local copy for researcher use (desktop, laptop) Local cop(ies) for access and preservation (UNL Library Data Repository) Off-site copy for disaster recovery (UNL ITS, cloud storage) Access through a domain repository (DRYAD) RETENTION & PRESERVATION

28 Disciplinary repositories exist for many areas of study ( ) DataCite - to find, access, and reuse data. Its listing, DataBIB ( is a tool to identify and locate online repositories of research data. Users and bibliographers create and curate records that describe data repositories that users can search Digging into Data - list of digital libraries, data archives and repositories ( 7/Default.aspx) re3data.org registry - research data repositories from all academic disciplines ( UNL Data Registry - deposit and register your data, even if it is not stored in our repository, to improve its discovery ( DOMAIN REGISTRIES/REPOSITORIES

29 DATA RETENTION & PRESERVATION IN A PLAN Physical specimens: The Laboratory retains soil samples in cold storage for five years, and frozen specimens used for PCR amplifications indefinitely. The Laboratory retains metadata associated with physical specimens indefinitely. Digital images, and nucleotide sequences, sequence alignments, and trees: Digital images (TIFF masters), nucleotide sequences, and associated metadata will be archived indefinitely in UNL s centralized data storage repository, a secure, lowcost and stable data archive, operated by UNL Libraries on behalf of the research faculty. The archive s terms of service include regular checks of data integrity. The proposal budget includes, in the final budget year, the one-time cost for 500 GB of storage.

30 Subject librarians - assist with data management planning ( Guide to data management ( Website covering data management ( ADDITIONAL RESOURCES

31 Visiting scholar Karla Strieb (Ohio State) 22 April 2014, 2p Unity Room (202), Gaughan Multicultural Center Panel of UNL faculty, administrators, and Strieb will discuss efforts at UNL to comply with the federal mandate regarding data access and sharing LEARN MORE ABOUT FEDERAL FUNDERS EXPECTATIONS

32 Describe the data you are going to collect include file formats and metadata standards (if known) How will the data be maintained? Back-ups, multiple copies, other options who will do this? Will there be public access to the data? If so, how and when? Are there any privacy concerns how will you address these? Where do you plan to deposit your data? How long will the data be maintained and available? If longterm, what are the provisions for long-term management? Budget considerations for data maintenance? your plans to: ASSIGNMENT: CREATE A DATA MANAGEMENT PLAN