Guidelines on RDM

This guide is intended to support the UiTM community in effective research data management throughout the data lifecycle of data planning, documenting, storage, sharing, and long-term preservation.

A formal DMP helps researchers plan their study project and data before, during, and after research project. It aims to collect, document, make accessible, and preserve data for future use.

In all research data lifecycle phases, the DMP should address these questions.

“How do I manage my data during this phase?”

“What type of data am I creating & managing?”

“How long do I store the data and how will

Samples of DMP are:
  • Guidelines on FAIR Data Management in Horizon 2020 –Europe Open Science Cloud (EOSC)
  • Australia National Data Service (ANDS) Data Management

  • How you organize data

  • How you organize your website bookmarks?
  • How you organize files and folder on gadget / phone / laptop?
  • How you organize your working profile?
  • How you organize annual work targets?
  • How you organize your publication on website?
  • Data organization is the process of arranging and structuring data in a logical and meaningful way. It involves:

    Organize data identification

    the process of assigning a unique identifier to each piece of data. This identifier can be used to track data over time and across different systems.

    Organize data storage

    the process of storing and organizing digital information for future access. Data storage can be network-based, allowing multiple users and locations to access the data.

    Some steps in organizing data include:

    Organize your data as to be primary or secondary sourcing and retrieval collection

    The process of setting on how your data would be extracting data from internal and external sources. Data can be used for a variety of purposes, including risk management, portfolio management, and other business objectives.

    Organize data preparation for re-use

    The process to ensure that data is accurate and consistent so that the results of analytics, visualizations, and business intelligence applications are valid. The process to identify and fix data issues that otherwise might not be detected.

    Data can be stored in three ways:

  • Centralized: Data is stored at one common place for all.
  • Structured / decentralized : The data has many structures and stored in one place.
  • Distributed / Partitioned: dividing data into independent components. It involves partitioning data into smaller pieces.
  • Data organization also include:

  • Organize file format and contextual information.
  • Organize project directories to aid the storage and finding of files.
  • Organize naming files to enable logical grouping and/or chronological sorting within directories.
  • Organize the contents of files to facilitate analysis.
  • Organize data file version.

  • What is metadata, and why is it important?

    Simply said, metadata is data about data. It enables anyone who is interested in your data understand what it is and how to use it. Consider it an instruction manual that provides all of the facts about your data, allowing others to easily discover it and learn how to utilize it without having to contact you directly.

    15 elements of Dublin Core as below:

    Metadata are more useful when standards are used, enabling easier use and comparison by researchers in the relevant discipline. If you are sharing your data in a repository, then the metadata standards used will vary between repositories.

    No Title Description
    1 Title A name given to the resource.
    2 Subject The topic of the resource.
    3 Description An account of the resource.
    4 Creator An entity primarily responsible for making the resource.
    5 Publisher An entity responsible for making the resource available.
    6 Contributor An entity responsible for making contributions to the resource.
    7 Subject A point or period of time associated with an event in the lifecycle of the resource.
    8 Type The nature or genre of the resource.
    9 Format The file format, physical medium, or dimensions of the resource.
    10 Identifier An unambiguous reference to the resource within a given context.
    11 Source A related resource from which the described resource is derived.
    12 Language A language of the resource.
    13 Relation A related resource.
    14 Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant.
    15 Rights Information about rights held in and over the resource.

    Data Type Original Data Format Recommended Formats
    Text Hand-written, docx, wpd, odt, rtf, txt, html, xml, pdf xml, PDF/A, txt
    Tabular Simple csv, tsv, pipe-delimited, xls(x), ods, dif, xps csv
    Tabular Extensive sav (SPSS), sas7bdat or xpt (SAS), dta (STATA) csv, txt with setup file or associated script (r or m)
    Database mdb, dbf, sql, sqlite, db, db3, xml xml, sqlite
    Visual static: pdf, jpeg, tiff, png, gif, bmp, moving: mpeg, mov, avi, mxf PDF/A, tiff, JPEG2000, MPEG-4
    Audio wav(e), mp3, mp2, aiff, wma, aac, dct, flac, ogg wave,aiff
    Image JPEG (.jpeg, .jpg, .jp2) if original created in this format, GIF (.gif), TIFF other versions (.tif, .tiff), RAW image format (.raw), Photoshop files (.psd), BMP (.bmp), PNG (.png), Adobe Portable Document Format (PDF/A, PDF) (.pdf) TIFF 6.0 uncompressed (.tif)

    As a researcher, you should identify the likely retention period for your data as early as possible in the research and ensure that requirements for retention and disposal are met.You must also ensure that actions and decisions taken during the project facilitate long-term or permanent retention for data with enduring value to the research community or of wider public interest.

    Minimum retention periods

    Your research data needs to be kept for as long as required to:

    • meet any statutory or regulatory obligations (records legislation, funding agency guidelines, contractual arrangements with research partners)
    • meet the current needs of researchers
    • meet the future needs of researchers where these can reasonably be anticipated
    • satisfy expectations of the University in documenting research activity.

    Disposal

    The destruction of data must be irreversible with no chance of recovery later. Digital data should be destroyed by deleting or overwriting information, purging magnetic media through degaussing (exposure to a strong magnetic field), or destroying the physical media.

    Paper can be shredded using secure shredding. Extra care should be taken with sensitive or confidential information where a secure paper destruction service must be used.

    In all cases records relating to what was destroyed, when and how should be retained.

    Planning for long-term and permanent retention

    If you think that your data may be a candidate for long-term or permanent retention, you should be aware that decisions made at an early stage of the research project can limit your later ability to retain data in a usable form. For example:

    • Human ethics requirements and the nature of the consents you seek from participants will determine whether data can be re-used for future projects and in what ways.
    • Technology-based decisions relating to storage media, software, and digital file formats might impact upon the length of time that data can be easily retrieved and used.
    • Identifying issues like these around long-term and permanent retention is part of Data Management Plan.

    Research data that is going to be retained permanently should be deposited in UiTM Research Data Repository.

    (Source: Monash University, 2018)


    What is Data Storage?

    • Files and documents are recorded digitally and saved in a storage system for future use.
    • Data storage makes it easy to back up files for safekeeping and quick recovery in the event of an unexpected computing crash or cyberattack.


    Types of Confidential Data

  • Financial Information
  • Medical Information
  • Personal Information
  • Academic Records
  • Identifiable Human Subject Research
  • Industry Secrets
  • Patentable Research

  • Ownership of Intellectual Property (IP)

    Researcher should clarify ownership of and rights relating to research data before a project starts. Ownership and rights will determine how the data can be managed in the future, so these should be documented early in a project through data management planning.