Managing shared data is becoming increasingly important as we move towards an open data world. For sharable data to be actionable, it needs to be FAIR: findable, accessible, interoperable and re-usable.

The assessment of opportunities at smallholder farm household level to improve their livelihoods needs integration of validated standardised agricultural, poverty, nutrition and gender indicators in the quantitative characterisation of these households. This will allow us to assess how these welfare indicators vary across a farm household population and across different agro-ecological and socioeconomic conditions. Such data would also allow us to better assess how they may change over time.

Furthering such a standardization across all institutes within the CGIAR (who have been estimated to conduct baseline interviews with around 180,000 farmers per year) would allow for much easier application of big data method applications for analyzing the household level data themselves, as well as for linking these data to other larger scale information sources like spatial crop yield data, climate data, market access data, roadmap data, etc. The Big Data platform of the CGIAR has therefore stimulated an effort to define how a common core of a cross-sectional household survey focusing on rural households could look like, the so-called 100Q exercise (with 100Q standing for 100 Questions that that core should contain). The core survey should deliver key information around the agricultural activities and off farm income of the household, as well as key welfare indicators focusing on poverty, food security, dietary diversity and gender equity.

Within this effort a workshop was held in Rome, Italy, in December 2018, where a group of scientists from different centers of the CGIAR and partner institutions discussed how such a core approach for cross-sectional surveys could look, and what type of information should be captured. The CoP SED report 2019.001 is a reflection of this work

Many CGIAR gender scientists have a qualitative research background, including researchers in the agri-food systems research programs. This suggests untapped potential in terms of using qualitative gender data collected through Focus Groups Discussions (FGD), Key Informant Interviews (KII) and other forms of Participatory Action Research (PAR).

However, these datasets vary widely on how data is structured and the detail of documentation provided. By facilitating the tagging, findability and accessibility of quantitative and qualitative gender data The working group gender meets Big data aims to facilitate mixed methods research by providing opportunities for both qualitative and quantitative researchers to exchange insights and create a stronger dialogue. This report is the outcome of a mini-grant procided by the CoP on socio-economic data to the CGIAR Gender Platform late 2018 to identify and tag relevant gendered data sets.

The global food system is under pressure and is in the early stages of a major transition towards more transparency, circularity, and personalisation. In the coming decades, there is an increasing need for more food production with fewer resources. Thus, increasing crop yields and nutritional value per crop is arguably an important factor in this global food transition.

Biofortification can play an important role in feeding the world. Biofortified seeds create produce with increased nutritional values, mainly minerals and vitamins, while using the same or less resources as non-biofortified variants. However, a farmer cannot distinguish a biofortified seed from a regular seed. Due to the invisible nature of the enhanced seeds, counterfeit products are common, limiting wide-scale adoption of biofortified crops. Fraudulent seeds pose a major obstacle in the adoption of biofortified crops.

A system that could guarantee the origin of the biofortified seeds is therefore required to ensure widespread adoption. This trust-ensuring immutable proof for the biofortified seeds, can be provided via blockchain technology.