Shifting the Goalposts—From High Impact Journals to High Impact Data
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WHITE PAPER Shifting the goalposts—from high impact journals to high impact data Anja Gassner1, Luz Marina Alvare2, Zoumana Bamba3, Douglas Beare4, Marichu Bernardo5, Chandrashekhar Biradar6, Martin van Brakel7, Robert Chapman8, Guntuku Dileepkumar9, Ibnou Dieng10, Sufiet Erlita11, Richard Fulss12, Jane Poole13, Mrigesh Kshatriya11, Guvener Selim14 Reinhard Simon14, Kai Sonder12, Nilam Prasai2, Maria Garruccio8, Simone Staiger Rivas14, Maya Rajasekharan14 , Chukka Srinivasa Rao9 1 World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, PO Box 30677 Nairobi 00100 Kenya 2 International Food Policy Research Institute (IFPRI), 2033 K St, NW, Washington, DC 20006-1002 USA 3 International Institute of Tropical Agriculture (IITA), HQ-PMB 5320, Ibadan, Oyo State Nigeria 4 WorldFish, Jalan Batu Maung, Batu Maung, 11960 Bayan Lepas, Penang, Malaysia, PO Box 500 GPO, 10670 Penang, Malaysia 5 International Rice Research Institute (IRRI), DAPO Box 7777 Metro Manila 1301, Los Baños, Philippines 6 International Center for Agricultural Research in the Dry Areas (ICARDA, "Dalia Building 2nd Floor, Bashir El Kassar Street, Verdun, Beirut, Lebanon 1108-2010 P.O. Box 114/5055 Beirut, Lebanon" 7 International Water Management Institute (IWMI), P. O. Box 2075, Colombo, Sri Lanka, 127, Sunil Mawatha, Pelawatte, Battaramulla, Sri Lanka 8 Bioversity International, "HQ- Via dei Tre Denari 472/a 00057 Maccarese (Fiumicino) Rome, Italy" 9 International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324 Andhra Pradesh, India 10 Africa Rice Center (AfricaRice) 01 B.P. 2031, Cotonou, Benin 11 Center for International Forestry Research (CIFOR), HQ- Jalan CIFOR, Situ Gede Bogor (Barat) 16115, Indonesia, Mailing-P.O. Box 0113 BOCBD Bogor 16000, Indonesia" 12 International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera, México-Veracruz, El Batán, Texcoco CP 56130, Edo. de México, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico 13 International Livestock Research Institute (ILRI), HQ-PO Box 30709, Nairobi, 00100 , Old Naivasha Road, , Nairobi, Kenya 14 International Potato Center (CIP), Avenida La Molina 1895, La Molina, Apartado Postal 1558, Lima, Peru 15International Center for Tropical Agriculture (CIAT), Km 17, Recta Cali-Palmira Apartado Aéreo 6713, Cali, Colombia Contents Introduction .................................................................................... 3 Types of research data .................................................................... 4 Research data infrastructure across the centers ............................ 6 Success stories .............................................................................. 15 Barriers to mainstreaming data sharing ....................................... 18 Recommendations ........................................................................ 21 Key references .............................................................................. 24 PAGE - 2 - Introduction CGIAR is a global agriculture research partnership. Its science is carried out by the 15 research centers who are members of the CGIAR Consortium in collaboration with hundreds of partner organizations. Each member of the CGIAR Consortium has the mandate to contribute to the eradication of hunger and poverty at the global level by advancing research in development. Being funded mainly through public funds there is an obligation to extract maximum public good value from the research data the individual centers are collecting. With the exception of a few designated projects, in the past, data itself was merely seen as a means to an end, synthesized to produce selected knowledge products such as publications, technical manuals or policy briefs. Changing financial realities and the need to reach our aid targets with less available resources is leading to a shift in thinking for new ways to make scientific research, and research data, more available, reusable and reproducible. Sufficiently preserved and replicable data are more absolute than contemporaneously drawn conclusions and, if they are collected to address one scientific question, can later be applied for the solution of entirely different problems (Altman et al., 2006). A growing number of donors now require data sharing requirements in their standard grant contracts and open access to be applied to the research data of the work they fund. DFID and the European Commission are among those who are now adopting this policy. As one of the first custodians of development related data, the World Bank, launched an open data initiative in 2012. CGIAR itself followed this example and approved in March 2012 a policy that clarifies CGIAR research results, including data, are openly available and accessible by default – and that any deviation has to be justified. Open data is not a new concept for CGIAR, but in the past has largely remained linked to specific projects or core programs that are designed to collect and share data widely. In keeping with the changes to the amount, management and analyses of data, the role of scientists working in development, such as those at the CGIAR Centers, is changing. Previously, grant awards, and performance evaluations focused strongly on publication in high-impact journals. Fortunately, there is a rediscovery that the real currency of research and scientific knowledge –the data methods and ideas- are also important instruments, in their own right, to accelerate the impact. Our scientists are increasingly using their skills and their strategic advantage of being well integrated in farming communities to create well designed datasets for others to use. While there is no doubt that progress on development related research questions would accelerate with increased access to well documented and readily accessible data, the move also puts more pressure on the gatherers, compilers, analysts and keepers of the data. Because of previous emphasis on scientific publications only, research projects usually do not budget for the extra costs that occur for publishing and long-term storage of data. While projects adequately account for the costs of conducting research, including the collection and analysis of research data, they seldom include preparing of data and metadata and curation as part of the costs of the research process led alone long-term costs for data storage and preservation beyond the immediate lifetime of a project. Even more importantly the research nature of CGIAR makes it mandatory to ensure that the contributions of those individuals and organizations are recognized, whose reputations and careers depend on that recognition. Data generators have little opportunities to gain recognition from PAGE - 3 - publishing high value datasets under a performance evaluation system that strongly emphases scientific publications. The purpose of this white paper is to provide an overview of the ongoing initiatives at center level to respond to changing public expectations and to the challenge of improving the conduct of science by making research data widely available. We also attempt to provide a framework for implementing open access for research data to maximize CGIAR’s impact on development. The remainder of this paper proceeds as follows; firstly a summary of the diversity of research data produced by the centers is given, followed by an overview of the existing infrastructure for data management for each Center. Secondly, some of the limitations and barriers faced by the centers in their process to mainstream research data publishing are addressed. The paper concludes with recommendations for how these limitations and barriers can be tackled. Types of research data In close collaboration with national research institutions almost 10,000 scientists, researchers, technicians, are collecting, analyzing and synthesizing data on smallholder agricultural systems in Asia, Africa and Latin America. While the overall mandate of the CGIAR Centers is the same, each Center has their own research emphasis resulting in a vast variety of different kinds of research data. The following section does not attempt to give an exhaustive description of the data we produce, but rather to provide an overview of the main types and their characteristics. Long term trials Centers that are focusing on breeding of food crops and livestock need multiple location trials over many years before a new genotype can be fully evaluated, so do agroforestry and forestry trials that are working with slow growing perennials. Centers working more generally on combined systems research, natural resource management and climate change also have research covering decades in order to characterize and influence changes in these systems. These kinds of data are often collected in various consecutive projects and technical and scientific staff that collect and analyze the data can change. From a scientific point of view it is not desirable or useful to make the data available before meaningful intermediate results have been collected. One-off data collections Some data are project specific and aimed at answering specific research and/or development related questions, often analyzed and published as part of the project deliverables. Publication should be written within a reasonable timeframe after which the data can be publically released together with the publication. What is a reasonable timeframe does not only vary from researcher to researcher, but by discipline. Economics publishing moves much slower than other fields. It is not uncommon for