dc.description.abstract |
Research Data Management (RDM) refers to the collection, organization, validation, and
preservation of data for analysis, discovery, sharing, reuse and transformation.
RDM consists
of a number of diff
erent activities and processes
that include
creation of data, storage, security,
preservation, retrieval, sharing, and reuse
while
taking into account technical capabilities,
human resource capability, ethical considerations, legal issues and government
. T
he strategic
importance of RDM within agricultural research institutes is to: enable scrutiny of research
finding
s
, prevent duplication of effort by enabling others to use the same data; promote
innovation through retrieval, co
-
analysis of data, ensuring r
esearch data gathered is not lost or
destroyed, and
that the research
meet funders’ requirements.
The purpose of this study
was
to examine Research Data Management (RDM) in Kenya’s
agricultural research institutes with the view to proposing interventions
to imp
rove
management, sharing and re
use of agricultural research output. The objectives
of the study
were to
:
1)
assess the status of research data management in Kenya’s agricultural research
institutes;
and 2
)
to determine the legal and policy framework, ICT infrastructure and human
capital that is available to facilitate RDM in Kenya’s agricultural research institutes.
The study
was
underpinned by the
Community Capability Model (
CCM) framework (Lyon
,
Ball, Duk
e
and
Day,
2012) and Data Curation Centre (DCC)
L
ifecycle
M
odel (Higgins, 2008).
The study adopted pragmatism ontology
with
mixed methods epistemology that enabled the
researcher to collect quantitative data from a large sample of researchers
in
six
purpos
ively
selected research
institutes. Census was used
to select the respondents who consisted
of
directors
of institute
s
, heads of research, heads of IT and librarians.
Both quantitative and
qualitative data were collected.
Quantitative data was
analyzed
usi
ng SPSS to generate
descriptive and inferential statistics while the qualitative data was
analyzed
thematically.
The finding
s
of the study revealed that RDM legal framework
did not exist in the institutes
surveyed
;
the
RDM policies and regulations
were outdated
;
the institutes lacked
unit/department to coordinate functions
of
RDM;
there was
limited RDM awareness and
advocacy;
the institutes lacked
RDM security systems;
the institutes suffered from lack of or
inadequate
RDM guidelines on
standardization; technical infrastructure; skills and
collaborative partnerships
. Overall, the findings revealed that
RDM
was poorly managed
.
The
study recommend
ed among others, the e
stablish
ment
of a
formal data governance structure to address RDM issues
,
a
legislati
ve and policy framework for
RDM;
capacity building programs
and plans,
incentivisation of
researchers;
and a sound
technical infrastructure
. |
en_US |