Research Data Management


Research Data Management is the responsible stewardship of the data created or generated as part of a research project. 

These studies can be presented in the form of text, experimental measurements, statistical tables, multimedia (audio, video, photo), geospatial records, program code.

Data management includes planning and development of a research project; collection, analysis, data storage; documenting, archiving, organization of access; reuse of data.


Data Management Plan (DMP) is a requirement of most organizations that provide grants for research.

The tools for making DMP differ depending on the country of origin and the requirements of the grantor, for example: DMP Assistant (Canada), DMP Tool (USA), DMPOnline (UK, EU), Guidelines on FAIR Data Management in Horizon 2020 (EU).

Effective data manipulation involves structuring files, documenting the research process, and metadata.

File structuring requires creating a project folder and individual subpages with publication sources, statistical (experimental) data, research results (program code, data analysis tables, work text), and a README file.

Documentation of metadata, data analysis and transformation methodology provides an understanding of data and research process by all stakeholders.

Metadata information about the original data – describes the data and helps them to classify, organize and characterize.

The key elements of metadata are the definition and designation of indicators, units of their measurement, a brief description of the assessment methodology and data sources.

File names should be unique, informative, not very long. It is advisable to use a standardized form for different versions of documents.

Recommended items for file names:

➠  name of the project or the name of the researcher

➠  job type or date of file creation (YYYYMMDD)

➠  version of the document (example: V1, V1_2, V2)

  use of characters from sets A-Z, a-z, 0-9, hyphen, underscore and dot

Examples: MultivariteAnalysis_Part2_20190221.docx, Protsiuk_Thesis_V1.pdf, UkrStat _2000-2019.xlsx

Use the following data formats:

➠  Data Tables – CSV замість XLSX

  Text Data – TXT or PDF instead of DOC

➠  Databases – XML or SQLITE instead of MDB, DBF, SQL

➠  Visual – PDF, TIFF, JPEG2000, MPEG-4, WAVE, AIFF

Backing up information is used to store data and play it back in case of damage.


Custom programs for project management and file versions: GIT: GitHubGitLabBitBucketTrello.

Platforms for storing and sharing files: Open Science FrameworkGoogle DriveDropboxBox.

For the organization of sharing, unlimited or partial use of data, you can use open licenses Creative Commons. Users are able to freely use digital content with the consent of authors and other copyright owners.

Types of Creative Commons licenses.

Choosing a machine-readable license Creative Commons.

Search for content licensed under Creative Commons:

➠  using

➠  using Google Advanced Search / Additional settings / Rights to use

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