Abstract
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 improve management, sharing, and reuse of agricultural research output. The objectives of the study were twofold: to assess the status of research data management in Kenya's agricultural research institutes and to determine the legal and policy framework, ICT infrastructure, and human capital available to facilitate RDM in Kenya's agricultural research institutes. The findings of the study revealed that RDM legal framework did not exist in the institutes surveyed; the RDM policies and regulations were not updated as necessary; the institutes suffered from inadequacies of technical infrastructure, skills, and collaborative partnerships. The study recommended, among others, the establishment of a formal data governance structure to address RDM issues, institutional and policy framework for RDM, capacity building programs, incentives for researchers, and a sound technical infrastructure.
TopIntroduction
The purpose of this study is to examine Research Data Management (RDM) in Kenya’s agricultural research institutes with the aim of proposing interventions to improve management, sharing, and reuse of agricultural research output. Ray (2014) defines RDM as the collection, organization, validation, and preservation of data for analysis, discovery, sharing, reuse, and transformation. Whyte and Tedds (2011) on the other hand view RDM as the organization of data from its entry into the research cycle through to dissemination and archiving of valuable results. Fundamentally, RDM consists of different activities and processes associated with data creation, storage, security, preservation, retrieval, sharing, and reuse taking into consideration the technical capabilities, ethical considerations, legal issues, human resource capability, and government frameworks. RDM benefits researchers and research institutes in many ways (Lewis, 2010; Van den Eynden et al., 2011; and Dora and Kumar, 2015) such as:
- 1.
Ability to share research data, minimizing the need to repeat work in the field or laboratory;
- 2.
Research data gathered at considerable cost is not lost or inadvertently destroyed;
- 3.
Retrieval, comparison, and co-analysis of data from multiple sources can lead to powerful insights;
- 4.
New research themes can emerge from re-analysis of existing data or comparisons with new data;
- 5.
Long-term preservation of data provides for validation check of the data and thus enhances the credibility and transparency of the research data used;
- 6.
By opening research data sets for the public, there is visibility of the host institution and its researchers;
- 7.
Increase the impact and visibility of agricultural research on agricultural sector, food security and national economy;
- 8.
Leads to new collaborations between agricultural research data users and research data creators, and
- 9.
Leads to the proper curation, full utilization, preservation, and reuse of research results (Heidorn, 2011; Lyon, Patel, and Takeda, 2014).
Therefore, research data are valuable resources that must prudently be managed by research institutes (Ray, 2014).
TopContextualization
The focus of this study on agriculture is premised on the fact that Kenya’s agricultural sector is the mainstay of the country’s economy; it contributes 26% of the gross domestic product (GDP), accounts for 65% of the country’s total export, and provides more than 18% of formal and 70% of informal employment in rural areas (Kenya, Republic of: Ministry of Agricultural, Livestock and Fisheries, 2010; United Nations Environment Programme (UNEP), 2015; Kenya Agricultural Research Institute (KARI), 2012). Therefore, the Kenyan government attaches great importance to the agricultural sector. Consequently, the Kenya Agricultural and Livestock Research Organization (KALRO) was instituted per the Kenya Agricultural and Livestock Research Act (No.17 of 2013) to coordinate agricultural research in the country. However, the Act does not clearly define how data generated in the research institutes should be managed to ensure the continued preservation, long-term access, sharing, and re-use. Currently, 16 agricultural research institutes have been established under the Act (KALRO, 2016):
Key Terms in this Chapter
Data Curation: The organization and integration of data collected from various sources and it involves capturing, appraisal, description, preservation, access, use and reuse, and sharing of research data.
Kenya Agricultural and Livestock Research Organization: A government corporate body set up vide Kenya Gazette Supplement No. 29 (Act No.17) 0f 2013 to coordinate agricultural research in the country.
Research Data: Data that is collected for the purpose of analysis to produce original results in form of raw data, abstracts questionnaires, videotapes, audiotapes specimens among others.
Research Data Management: Organization of different activities and processes associated with creation, description, storage, preservation, access, reuse, sharing, security taking into account technical capabilities, ethical considerations, legal issues, human resource capability and government frameworks.
Data Literacy: Ability to Create, manipulate, read, understand, interpreter, and communicate data as information to the desired audience.
Agricultural Research Institute: An institute that its core mandate is to do research that appertains crop or livestock in order to improve its quality and quantity including setting its long and short ranges plans. Field of activities can include field crops, horticulture, animal production biotechnology, among others.
Agricultural Research Data: Collection, processing, and analysis of statistical data that characterize the current status and development of crops and livestock to be used to draw up long- and short-range plans for agricultural production.