Research Data Guide

Managing research data

Research data? Management of research data?

Research data can be

  • of variety of formats and content types like text, numerical, multimedia, models, software, discipline specific, instrument specific etc. or

  • variety of objects like documents (text, word), spreadsheets, laboratory notebooks, field notebooks, diaries, questionnaires, transcripts, codebooks, audiotapes, videotapes, photographs, films, test responses, slides, artefacts, specimens, samples, collection of digital objects acquired and generated during the process of research, statistical or other data files, database contents (video, audio, text, images), models, algorithms, scripts, contents of an application (input, output, logfiles for analysis software, simulation software, schemas), methodologies and workflows, standard operating procedures and protocols etc. 

Management of research data (RDM) refers to creating and storing research data and related descriptive metadata. The aim is to secure and preserve the usability and reliability of the material, taking into account confidentiality and data protection issues throughout the lifespan of the data.

Digital curation defined: "Digital curation is concerned with actively managing data for as long as it continues to be of scholarly, scientific, research and/or administrative interest, with the aim of supporting reproducibility of results, reuse of and adding value to that data, managing it from its point of creation until it is determined not to be useful, and ensuring its long-term accessibility and preservation, authenticity and integrity" (DCC)

  • adding value  to data sets
  • involves a wide range of stakeholders (learned societies, funders, repositories, libraries...)
  • is about risk management  (uncertanties into measurable and manageable risks)  and
  • about good data management practices

A research data management plan (DMP) is a document containing all aspects of your research data (e.g. what will you do with your research data (RD) during and after your research project). Writing a DMP should be started at the very beginning of a research project and it is a vital step in a research project helping to ensure that RD are accurate, complete, reliable, and secure both during and after research.

Benefits of managing research data

The benefits of managing your data include:

  • Meeting funding body grant requirements.
  • Ensuring research integrity and reproducibility.
  • Increasing your research impact.
  • Ensuring research data and records are accurate, complete, authentic and reliable.
  • Saving time and resources in the long run.
  • Enhancing data security and minimizing the risk of data loss.
  • Preventing duplication of effort by enabling others to use your data.
  • Complying with practices conducted in industry and commerce.

Facilitating the analysis of change, by providing data with which data at other points in time can be compared.

‚Äč(Research Data Management Training Mantra http://datalib.edina.ac.uk/mantra/)

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RDM practices in three stages

Before research project

  • create a DMP
  • address ethical and legal issues
  • consider RDM costs

During research project

  • update DMP
  • manage data (by daily basis)
  • organize and document data
  • take care of the security of the data

At the end/after research project

  • choose which data to retain and archive
  • preserve and retain data
  • deposit data to suitable archive or repository
  • obtain DOI
  • include data accession statement in publications

Research data life cycle

Data collection

What kind of data are collected is mainly determined by the research questions. Research data are typically questionnaire surveys, interviews, focus group discussions, written material, visit or meeting recordings, official documents, archival material, websites, or register or media data.

Data collection methods are determined by the type of data sought for.

  • Quantitative data can be collected through interviews, postal or online questionnaires, by using existing source material, or by measuring.
  • Qualitative data are often collected by recording individual interviews, group interviews, sessions or meetings as audio or video files.
  • Written material collection is usually initiated by publishing writing requests or invitations, and then collecting the writings via email, post or a specifically created website.
  • Official documents can nowadays often be obtained from the Internet but some are available only by request or by obtaining permission to use them for research purposes.

Access to register data generally requires applying for permission. More information on how to apply for access to register data on the Finnish Information Centre for Register Research web site.

Researchers and research teams can collect the data themselves or can contract a data collection company to do it. If data collection is contracted out, it is best to send the call for tender to several companies. Data management plans are useful for drawing up tender calls.

Source: Finnish Social Science Data Archive

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