Research Data Publishing

Data publishing involves digital dissemination of research data and supporting information such as metadata, documentation, models, code and unpublished reports in such a way that it is persistently and uniquely identifiable. In the past research data was not viewed as a central component of scholarly communication or counted as a core research output such as peer reviewed journal articles for example. However in the last number of years there is a growing emphasis of publication of research data as a principle research output. The Data Citation Principles state that “Data should be considered legitimate, citable products of research”. This seminar will look into the why, how, where and when of data publishing, from a CGIAR point of view, including an introduction to scholarly publishing through peer reviewed data papers

Data management support pack

This pack is designed to help you produce high quality, reusable and open data from your research activities. It consists of documents, templates and videos covering the different aspects of data management and ranging from the overarching concepts and strategies through to the day-to-day activities. For each of the videos in the pack we have included a transcript of the narrative. The Data Management Support Pack was created to support the implementation of the CCAFS Data Management strategy

Where is my crop? Data-driven initiatives to support integrated multi-stakeholder agricultural decisions

Globally, there has been an explosion of data generation in agriculture. With such a deluge of data available, it has become essential to create solutions that organize, analyze, and visualize it to gain actionable insights, which can guide farmers, scientists, or policy makers to take better decisions that lead to transformative actions for agriculture. There is a plethora of digital innovations in agriculture that implement big data techniques to harness solutions from large amounts of data, however, there is also a significant gap in access to these innovations among stakeholders of the value chains, with smallholder's farmers facing higher risks. Open data platforms have emerged as an important source of information for this group of producers but are still far from reaching their full potential. While the growing number of such initiatives has improved the availability and reach of data, it has also made the collection and processing of this information more difficult, widening the gap between those who can process and interpret this information and those who cannot. The Crop Observatories are presented in this article as an initiative that aims to harmonize large amounts of crop-specific data from various open access sources to build relevant indicators for decision making. Observatories are being developed for rice, cassava, beans, plantain and banana, and tropical forages, containing information on production, prices, policies, breeding, agronomy, and socioeconomic variables of interest. The Observatories are expected to become a lighthouse that attracts multi-stakeholders to avoid “not see the forest for the trees” and to advance research and strengthen crop economic systems. The process of developing the Observatories, as well as the methods for data collection, analysis, and display, is described. The main results obtained by the recently launched Rice Observatory (www.riceobservatory.org), and the about to be launched Cassava Observatory are presented, contextualizing their potential use and importance for multi-stakeholders of both crops. The article concludes with a list of lessons learned and next steps for the Observatories, which are also expected to guide the development of similar initiatives. Observatories, beyond presenting themselves as an alternative for improving data-driven decision making, can become platforms for collaboration on data issues and digital innovations within each sector

Analysis and evaluation of socio-technical innovation bundles dashboard

This executive summary provides an overview of an Inventory of available gender and socio-economic datasets, data and tools that could facilitate bundling. To achieve this output, we; (1). Collected and curated relevant information on STIBs that promote women’s empowerment and resilience. (2). Designed the layout to effectively visualize the content and demonstrate the platform’s functionality. (3). Present the design and layout of available STIBs datasets (4). Define and cluster different socio-technical bundles in the available gender and socio-economic datasets and visualize them. Work Package 2 (WP2) of the CGIAR Global Initiative on Gender Equality (HER+) seeks to identify and co-design socio-technical innovation bundles (STIBs) for women’s empowerment and resilience. The output of this activity is led by the ABC in collaboration with (IRRI) and the International Water Management Institute (IWMI). This output report details the inventory of gender and socio-economic datasets, data, and tools that can be used to design inclusive STIBs. These bundles are categorized and clustered based on different socio-technical factors. In addition, a dashboard that includes an interactive map and repository has been developed to visualize this information

Surveillance and diagnostics of the emergent Sri Lankan cassava mosaic virus (Fam. Geminiviridae) in Southeast Asia

Emergent agricultural pathogens cause severe damage worldwide and their invasive potential is significantly increased by global trade, crop intensification and climate change. Standard surveillance and diagnostic protocols need to be evaluated and implemented, particularly with diseases caused by a wide range of pathogens that induce similar symptoms. Such is the case with Cassava Mosaic Disease (CMD) present in Africa and Asia, and associated with mixed virus infections and recombinant and re-assorted virus strains. CMD has been recently reported in Southeast Asia (SEA) and is already widely spread throughout this region. This communication offers an update on protocols and tools used to track the distribution of CMD and to characterize the pathogen associated with it in SEA

The ontologies community of practice: a CGIAR initiative for Big Data in agrifood systems

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams

Data and Information Management Tools for the CGIAR Gender and Agriculture Research Network

The purpose of this webinar was to showcase how members of the CGIAR Gender and Agriculture Research Network can use two data management tools recently developed by CIAT. 1 June 201

Research data sharing

Presented by Leroy Mwanzia, CIAT at the 5th Webinar of the CGIAR Gender and Agriculture Research Network, 2016