Discuss the Importance of Data Management in Research

1. Definiton of Key terms

Data management is a general term which refers to a part of research process involving organising, structuring, storage and care of data generated during the research process. It is of prime importance in that it is part of good research practice and it has a bearing on the quality of analysis and research output. The University of Edinburgh (2014) defines data management as a general term covering how you organize, structure, store and care for data used or generated during the lifetime of a research project.

Data refers to information obtained from experiments, surveys, observations, interviews, and any other data collection method. It can be viewed as raw facts and statistics of any kind collected or produced in the course of research for reference and analysis. CGIAR (2017) defines research data as records of facts which are primarily referred and accepted for research findings. This data can take several forms, formats, sizes and complexity.

Research can be defined as a systematic collection, documentation, analysis and dissemination of information which increases knowledge capital in a specific or broad subject matter.

1.1 The importance of Data Management

Damien Chaussabel et al (2009) highlight that “data management is critical because it ensures that once data it is collected, information is and remains secure, interpretable and exploitable…..”(pg1225).Management of data is done through various software and hardware. The process of data management is important in ensuring that data is not lost, not inadvertently changed, and cannot be manipulated, and to ensure that research data remain traceable, accessible and usable by others in the same research or in other similar researches. Lessing & Scheepers (2001) cited in Maritz(2003) are of the view that managing data is of importance in that it determines a projects success or failure and data in any organisation is a resources or asset which should be efficiently used. The data undergoes through different stages such as raw data, cleaned up, processed, analysed and data management is undertaken in each stage of the process its usage depending on the purposes of the research(Van Berchum & Grootveld, 2017,cited by CESSDA training team(2017-2020). Effective data management takes into account the researchers technical capacity in all respects and it begins with taking into account purposes of data collection, stakeholders and reuse potential of data. This is reflected in a data management plan. The importance of data management is discussed below:

1. Validation and Verification of research results
   Data management allows other researchers to validate and verify published results. The fact that through data management, data can be shared and it retains its futuristic use signifies the importance of data management in any research process. The probability that data will be verified or validated increases the responsibility on researchers which in turn improves the accuracy and reliability of research data. Dunie, Matt (2017) emphasises the role of data management in maintaining the integrity of data in research. Research data management should also ensure the practical use of data on the long term and enable sharing of data for reuse, since you will be working together with others during your research or because others may build on or continue your research after completion of your research project. Data used in any research if properly managed can have a longer lifespan.
2. Meeting Requirements of Research organisations, Publishers and Funders
   Data management has also gained prominence in research due to the expectation and demands of research organizations and research funders that collected data should be provided as one of their requirements in funding or supporting a research. Given this requirement it becomes very essential and critical that researchers come up with a well laid out data management process to facilitate its storage and possibility of sharing it with other researchers. Most of these funders expect researchers to make it relevant and necessary that result from publicly funded research are freely available to other researches as secondary data. Thus data management helps save public resources be reducing chances of repetitive collection of data. Thus data management can be used as one of the ways to secure and retain funding for researches .Research funders are now prioritizing sharing of research data and making one’s data management process a consideration before accepting or taking on board a research proposal. Just like funders, publishers of research work also expect to be provided with research data thus data management helps researchers to satisfy the data preconditions of publishers.
3. Risk Management
   Data management assists in the risk management in research. Data is susceptible to risk such as data loss, corruption and breaching copying right as well intellectual property laws .Thus data management prevents and mitigate such risks and their potential impact which can be detrimental to the whole research. This role of data management is shared by Borghi et al (2017) who further highlight that failure to properly manage data can result in loss of data, inaccessibility of data, loss of credibility of the researcher and associated organisations in the end damaging their reputation. Furthermore poor data management can lead to misalignment of resources and duplication of research efforts.
4. Data is used for other researches and Protection of intellectual property.
   Data used in any research if properly managed can have a longer lifespan than the project which they were initially collect for implying that its usage can be beyond the project. In an organisation or project where there is proper data managements the collected data on any research can still be analysed or reused for other research projects which are similar or different to the one which the data was collected for giving research data multi-lifecycle. Thus data management contributes to knowledge capital and can facilitate innovation without necessarily embarking on new data collection. Data managements thus facilitate sharing of research data. With data management researchers can get due credit and protect their intellectual property where the data is used by others. Not only do researchers get credit but it’s also raises their profile and reputation in the research filed
5. Easy Accessibility and understanding
   Research data which is organized and properly stored is easy to access and understand thus data management’s saves on time and resources this is especially true where data management is done through research packages such as SPSS and excel. Computerised Statistical package makes data management easy through data manipulation functionalities like summarization, descriptions and regression analysis.
6. Protection of Personal/sensitive information
   Research usually involves collection of sensitive personal information of research participants. This is especially true for social science research which involves humans and potentially asks private information like health status and preferences. For a researcher to be able to reduce chances of data leakage and potentially exposing stakeholders private or sensitive information data management has to be enhanced(Mosley et al,2010). This importance of data management also applies to research which involves sensitive organisational matters like governments either in terms of security of participants or organisations ,which good data management collected information will be secure thus protecting research participants as well as the researchers form ethical scrutiny and legal repercussions of unwarranted disclosures of research data.

1.2 Conclusion

The view taken by CGIAR (2017) that data management is not an end or outcome in itself but rather a stepping stone to research knowledge capital accumulation and innovation brings out the importance of effective data management in research and that it should be premised on the principles of being findable, interoperable, accessible and reusable. As discussed in this paper data management is of critical importance in the research process and in all stages from planning, data collection, organising, storage, analysis and sharing of research findings as data management is major determinant of the research output and analysis, and also given data’s multi lifecycle the management of the same cannot be overlooked. Data management is important to research however it faces many challenges such as non-priorisation of the process, lack of funding and technical incapacity thus for projects to derive maximum benefit and realise the significance of data management these challenges have to be addressed. The reason for data management can be summarised as avoiding unnecessary duplication, result validation, research impact and visibility to the research community, avoiding data loss, meeting funding requirements and risk management.

References

1. A Research Data Management Guide for Researchers(2017) John A Borghi, Stephen Abrams, Daniella Lowenberg, Stephanie Simms, John Chodacki.
2. CESSDA Training Team (2017 - 2020). CESSDA Data Management Expert Guide.
3. Bergen, Norway: CESSDA ERIC. Retrieved from https://www.cessda.eu/DMGuide.
4. CGIAR Internal Audit Unit (2017) Research Data Management Good Practice Note https://storage.googleapis.com/cgiarorg/2018/01/GPN-Research-Data-Management-Sept-2017.pdf accessed 14/06/2020.
5. Data management: it starts at the bench (2009).Damien Chaussabel, Hideki Ueno, Jacques Banchereau & Charles Quinn nature immunology volume 10 numbers 12 December 2009.
6. DAMA guide to the data management body of knowledge (2010)Mosley, Mark. Brackett, Michael H. Earley, Susan. Henderson, Deborah. Data Administration Management Association [Corporate Author].
7. Dunie, Matt. ‘The Importance of Research Data Management (2017): The Value of Electronic Laboratory Notebooks in the Management of Data Integrity and Data Availability’. 1 Jan. 2017: 355 – 359.
8. Lori M. Jane and Andrew Asher the Problem of Data: Data Management and Curation Practices among University Researchers.
9. Maritz SG (2003) Data management: managing data as an organisational resource Acta Commercii 2003 Volume 3, London.
10. University of Edinburgh Information Services. Research data management programme: research data management home [Internet]. Edinburgh, UK: The University; Sep, 2014. < http://www.ed.ac.uk/schools-departments/information-services/research-support/data-management/data-management-home>.
11. Veerle Van den Eynden, Louise Corti, Matthew Woollard, Libby Bishop and Laurence Horton. Managing and sharing data. First published 2009 Third edition, fully revised, 2011 UK Data Archive University of Essex Wivenhoe Park Colchester Essex CO4 3SQ.

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