Research data management in Turkey: perceptions and practices
| Pages | 271-289 |
| Date | 19 June 2017 |
| DOI | https://doi.org/10.1108/LHT-11-2016-0134 |
| Published date | 19 June 2017 |
| Author | Arsev Umur Aydinoglu,Guleda Dogan,Zehra Taskin |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Information user studies,Metadata,Information & knowledge management,Information & communications technology,Internet |
Research data management in
Turkey: perceptions and practices
Arsev Umur Aydinoglu
Middle East Technical University, Ankara, Turkey, and
Guleda Dogan and Zehra Taskin
Hacettepe University, Ankara, Turkey
Abstract
Purpose –The massive increase in research data being produced nowadays has highlighted the importance
of research data management (RDM) to science. Research data not only have to be cost effective but also
reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the
perceptions and practices of Turkish researchers on the subject of RDM.
Design/methodology/approach –An online survey was distributed to the academicians in 25 universities
in Turkey, and 532 responses were gathered.
Findings –Results indicate that although Turkish researchers are aware of the benefits of data
management, are willing to share their research data with certain groups, and have decent preservation
habits, they express that they lack the technical skills and knowledge needed for RDM. In addition,
no institutionalized support (staff, training, software, and hardware) is provided to researchers.
Research limitations/implications –A well-structured data strategy or policy that includes resource
allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is
required for better data management practices among researchers in Turkey.
Originality/value –This is the first study that investigates the data practices of Turkish academics who
produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the
growing literature on RDM.
Keywords Data preservation, Research data management, Data storage, Data repository, Data sharing,
Research data
Paper type Research paper
Introduction
With the penetration and suffusion of information and communication technology (ICT) in
our lives, scientific research has evolved as well. As such, scientific research is more data
intensive and derives information from massive volumes of digitized data. As of 2013,
2.5 quintillion bytes of data are being produced every day (www-01.ibm.com/software/data/
bigdata/what-is-big-data.html), 90 percent of which was produced in the last two years
(SINTEF, 2013). A correct assumption is that the amount of data being produced will
continue to increase. For instance, internet users numbered 2.8 billion in 2013, whereas
today, they number more than 3.5 billion (www.internetlivestats.com/internet-users/).
The use of social media has increased the amount of data being produced. The total amount
of data in the world is expected to be 4.1 zettabytes in 2016 and is estimated to be
40 zettabytes in 2020. Therefore, data management has become an important issue.
Likewise, in the scientific arena, data have become so prominent that it has been given
anewnamein“The Fourth Paradigm: Data-Intensive Scientific Discovery”in which
“allofthescienceliteratureisonline,allofthe science data is online, and they interoperate
with each other”(Hey et al., 2009). In previous paradigms scientific activities were driven
Library Hi Tech
Vol. 35 No. 2, 2017
pp. 271-289
© Emerald PublishingLimited
0737-8831
DOI 10.1108/LHT-11-2016-0134
Received 23 November 2016
Revised 22 February 2017
Accepted 30 March 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0737-8831.htm
The study was funded through the TÜBİTAK-Marie Curie FP7 Co-funded Brain Scheme (Project
No. 114C011). The funders had no role in study design, data collection and analysis, decision to publish,
or preparation of the paper. The authors would like to acknowledge the DataONE Usability and
Assessment Group for preparing the original survey and sharing their survey and data sets from the
original study with public.
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Research data
management
in Turkey
by experimentation, theory, and computation (Hey et al., 2009). The traditional hypothesis-
based scientific approach has been gradually replaced by the analyses of electronic
databases that can hold large amounts of information. As papers, lab books, tapes, and
photographic films have moved to digital archives, cloud storages, and data warehouses,
science has gone beyond the boundaries of hypotheses. Analyses are built on the
collections themselves, and patterns, anomalies, and diversities on which questionswill be
posed later are sought. Hence, the term “data-intensive science”has emerged, and this
practice derives information from the data sets collected by various computerized
modeling and simulation systems, imaging devices, sensors and sensor networks, and
other data gathering and storage techniques (Hey et al., 2009; Knyazkov et al., 2012).
The vision is to have “all of the science literature online, all of the science data online,
and interoperate with each other”(Hey et al., 2009).
These mega-scale databases consist of data captured by various novel scientific tools,
sometimes on a real-time basis. With this continuous flow of electronic information, the
need to collect, store, curate, integrate, and analyze data in a way that could help
inter-institutional and interdisciplinary collaboration has gained importance for the
advancement of science in the twenty-first century.
According to Birnholtz and Bietz’s (2003, p. 339) study, data are an evidence for
validation of scientific contribution and it makes a social contribution to the establishment
of practice. Therefore, understanding the importance of the data is vital to design, sustain,
and curate well-structured RDM systems. In the light of all these developments and rising
importance of “RDM”subject, this paper aims to reveal the perceptions and practices of
Turkish researchers on the subject of RDM. In a nutshell, the current study addresses the
question of the perceptions toward and practices of RDM in Turkey. Main research
questions are as follows:
RQ1. What are the common research data types and formats among Turkish scholars?
RQ2. To whom and what degree research data are shared in Turkey?
RQ3. What are the main reasons for not sharing research data with others?
RQ4. What are the most preferred places to store the data?
RQ5. What is the awareness level of scholars about the benefits of data sharing?
RQ6. What are the current conditions and facilities provided by universities or research
institutions for RDM?
According to research questions, current condition for RDM in Turkey evaluated from two
angles; skills/awareness levels of scholars and current policies on research data. As first five
research questions aim to reveal skills and awareness levels of scholars about data
management, the last question is designed to understand the approaches of decision makers
and managers. Answers of the research questions are grouped in the discussion section to
provide general framework on research data approaches in Turkey.
Literature review
Various techniques and tools are required to analyze data sets. High-performance
computers and advanced software help scientists to process large arrays of data sets to
produce results that could be later reused, tested, and verified. High-quality data sets,
if stored in a way which facilitate the instantaneous global access, could be used anywhere,
anytime, thereby resulting in new scientific theories and studies.
The literature on RDM is growing rapidly. Current studies focus on understanding the
current situation, storing research data, the role of libraries and data warehouses in the
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