Making open data work for plant scientists

Digitising biopiracy? The global governance of plant genetic resources in the age of digital sequencing information

Historical concerns over the exploitation of the Global South's genetic biodiversity framed the importance of creating global governance mechanisms to ensure fair access to and benefit-sharing of genetic resources worldwide. The Convention on Biological Diversity (CBD) and International Treaty on Plant Genetic Resources for Food and Agriculture (Plant Treaty) came into existence over the past three decades to redress the centuries of genetic exploitation of the Global South. Both of the treaties explicitly regulate and facilitate the exchange of physical genetic material. The recent emergence of relevant digital technologies, such as digital sequencing information (DSI), could make both treaties irrelevant. This article analyses the current state of the CBD and Plant Treaty as it relates to global agricultural research in light of DSI. I argue that DSI presents less of a threat to exacerbating historical gene flows than it does to the further displacement of public sector research by the private sector. The article then suggests looking at the lessons from open-source approaches to counter the privatisation of DSI and related gene flows. I draw on 11 key informant interviews with country negotiators involved with the CBD and Plant Treaty as well as a review of official reports from both frameworks.

AgroFIMS: A Tool to Enable Digital Collection of Standards-Compliant FAIR Data

Agricultural research has been traditionally driven by linear approaches dictated by hypothesis-testing. With the advent of powerful data science capabilities, predictive, empirical approaches are possible that operate over large data pools to discern patterns. Such data pools need to contain well-described, machine-interpretable, and openly available data (represented by high-scoring Findable, Accessible, Interoperable, and Reusable—or FAIR—resources). CGIAR's Platform for Big Data in Agriculture has developed several solutions to help researchers generate open and FAIR outputs, determine their FAIRness in quantitative terms1, and to create high-value data products drawing on these outputs. By accelerating the speed and efficiency of research, these approaches facilitate innovation, allowing the agricultural sector to respond agilely to farmer challenges. In this paper, we describe the Agronomy Field Information Management System or AgroFIMS, a web-based, open-source tool that helps generate data that is “born FAIRer” by addressing data interoperability to enable aggregation and easier value derivation from data. Although license choice to determine accessibility is at the discretion of the user, AgroFIMS provides consistent and rich metadata helping users more easily comply with institutional, founder and publisher FAIR mandates. The tool enables the creation of fieldbooks through a user-friendly interface that allows the entry of metadata tied to the Dublin Core standard schema, and trial details via picklists or autocomplete that are based on semantic standards like the Agronomy Ontology (AgrO). Choices are organized by field operations or measurements of relevance to an agronomist, with specific terms drawn from ontologies. Once the user has stepped through required fields and desired modules to describe their trial management practices and measurement parameters, they can download the fieldbook to use as a standalone Excel-driven file, or employ via free Android-based KDSmart, Fieldbook, or ODK applications for digital data collection. Collected data can be imported back to AgroFIMS for statistical analysis and reports. Development plans for 2021 include new features such ability to clone fieldbooks and the creation of agronomic questionnaires. AgroFIMS will also allow archiving of FAIR data after collection and analysis from a database and to repository platforms for wider sharing.

How to build an effective research network: lessons from two decades of the GARNet plant science community

Successful collaborative research is dependent on excellent ideas and innovative experimental approaches, as well as the provision of appropriate support networks. Collaboration requires venues, infrastructures, training facilities, and, perhaps most importantly, a sustained commitment to work together as a community. These activities do not occur without significant effort, yet can be facilitated and overseen by the leadership of a research network that has a clearly defined role to help build resources for their community. Over the past 20 years, this is a role that the UKRI-BBSRC-funded GARNet network has played in the support of the UK curiosity-driven, discovery-led plant science research community. This article reviews the lessons learnt by GARNet in the hope that they can inform the practical implementation of current and future research networks.

Making experimental data tables in the life sciences more FAIR: a pragmatic approach

Making data compliant with the FAIR Data principles (Findable, Accessible, Interoperable, Reusable) is still a challenge for many researchers, who are not sure which criteria should be met first and how. Illustrated with experimental data tables associated with a Design of Experiments, we propose an approach that can serve as a model for research data management that allows researchers to disseminate their data by satisfying the main FAIR criteria without insurmountable efforts. More importantly, this approach aims to facilitate the FAIR compliance process by providing researchers with tools to improve their data management practices.

The grant is dead, long live the data - migration as a pragmatic exit strategy for research data preservation

Open research, data sharing and data re-use have become a priority for publicly- and charity-funded research. Efficient data management naturally requires computational resources that assist in data description, preservation and discovery. While it is possible to fund development of data management systems, currently it is more difficult to sustain data resources beyond the original grants. That puts the safety of the data at risk and undermines the very purpose of data gathering.

PlaSMo stands for ‘Plant Systems-biology Modelling’ and the PlaSMo model repository was envisioned by the plant systems biology community in 2005 with the initial funding lasting until 2010. We addressed the sustainability of the PlaSMo repository and assured preservation of these data by implementing an exit strategy. For our exit strategy we migrated data to an alternative, public repository with secured funding. We describe details of our decision process and aspects of the implementation. Our experience may serve as an example for other projects in a similar situation.

We share our reflections on the sustainability of biological data management and the future outcomes of its funding. We expect it to be a useful input for funding bodies.

The Future of Digital Sequence Information for Plant Genetic Resources for Food and Agriculture

The recent debates on the legal status of "digital sequence information" (DSI) at the international level could have extensive consequences for the future of agriculture and food security. A large majority of recent advances in biology, medicine, or agriculture were achieved by sharing and mining of freely accessible sequencing data. It is most probably because of the tremendous success of modern genomics and advances of synthetic biology that concerns were raised about possible fair and equitable ways of sharing data. The DSI concept is relatively new, and all concerned parties agreed upon the need for a clear definition. For example, the extent to which DSI understanding is limited only to genetic sequence data has to be clarified. In this paper, I focus on a subset of DSI essential to humankind: the DSI originating from plant genetic resources for food and agriculture (PGRFA). Two international agreements shape the conservation and use of plant genetic resources: the Convention on Biodiversity and the International Treaty for Plant Genetic Resources for Food and Agriculture. In an attempt to mobilize DSI users and producers involved in research, breeding, and conservation, I describe here how the increasing amount of genomic data, information, and studies interact with the existing legal framework at the global level. Using possible scenarios, I will emphasize the complexity of the issues surrounding DSI for PGRFA and propose potential ways forward for developing an inclusive governance and fair use of these genetic resources.

Practical steps to digital organism models, from laboratory model species to 'Crops in silico

A recent initiative named 'Crops in silico' proposes that multi-scale models 'have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts' in plant science, particularly directed to crop species. To that end, the group called for 'a paradigm shift in plant modelling, from largely isolated efforts to a connected community'. 'Wet' (experimental) research has been especially productive in plant science, since the adoption of Arabidopsis thaliana as a laboratory model species allowed the emergence of an Arabidopsis research community. Parts of this community invested in 'dry' (theoretical) research, under the rubric of Systems Biology. Our past research combined concepts from Systems Biology and crop modelling. Here we outline the approaches that seem most relevant to connected, 'digital organism' initiatives. We illustrate the scale of experimental research required, by collecting the kinetic parameter values that are required for a quantitative, dynamic model of a gene regulatory network. By comparison with the Systems Biology Markup Language (SBML) community, we note computational resources and community structures that will help to realize the potential for plant Systems Biology to connect with a broader crop science community.

The politics of data friction

Purpose

The purpose of this paper is twofold: first, to further develop Paul Edwards’ concept of “data friction” by examining the socio-material forces that are shaping data movements in the cases of research data and online communications data, second, to articulate a politics of data friction, identifying the interrelated infrastructural, socio-cultural and regulatory dynamics of data friction, and how these are contributing to the constitution of social relations.

Design/methodology/approach

The paper develops a hermeneutic review of the literature on socio-material factors influencing the movement of digital data between social actors in the cases of research data sharing and online communications data. Parallels between the two cases are identified and used to further develop understanding of the politics of “data friction” beyond the concept’s current usage within the Science Studies literature.

Findings

A number of overarching parallels are identified relating to the ways in which new data flows and the frictions that shape them bring social actors into new forms of relation with one another, the platformisation of infrastructures for data circulation, and state action to influence the dynamics of data movement. Moments and sites of “data friction” are identified as deeply political – resulting from the collective decisions of human actors who experience significantly different levels of empowerment with regard to shaping the overall outcome.

Research limitations/implications

The paper further develops Paul Edwards’ concept of “data friction” beyond its current application in Science Studies. Analysis of the broader dynamics of data friction across different cases identifies a number of parallels that require further empirical examination and theorisation.

Practical implications

The observation that sites of data friction are deeply political has significant implications for all engaged in the practice and management of digital data production, circulation and use.

Social implications

It is argued that the concept of “data friction” can help social actors identify, examine and act upon some of the complex socio-material dynamics shaping emergent data movements across a variety of domains, and inform deliberation at all levels – from everyday practice to international regulation – about how such frictions can be collectively shaped towards the creation of more equitable and just societies.

Originality/value

The paper makes an original contribution to the literature on friction in the dynamics of digital data movement, arguing that in many cases data friction may be something to enable and foster, rather than overcome. It also brings together literature from diverse disciplinary fields to examine these frictional dynamics within two cases that have not previously been examined in relation to one another.

How Does One "Open" Science? Questions of Value in Biological Research

Open Science policies encourage researchers to disclose a wide range of outputs from their work, thus codifying openness as a specific set of research practices and guidelines that can be interpreted and applied consistently across disciplines and geographical settings. In this paper, we argue that this "one-size-fits-all" view of openness sidesteps key questions about the forms, implications, and goals of openness for research practice. We propose instead to interpret openness as a dynamic and highly situated mode of valuing the research process and its outputs, which encompasses economic as well as scientific, cultural, political, ethical, and social considerations. This interpretation creates a critical space for moving beyond the economic definitions of value embedded in the contemporary biosciences landscape and Open Science policies, and examining the diversity of interests and commitments that affect research practices in the life sciences. To illustrate these claims, we use three case studies that highlight the challenges surrounding decisions about how--and how best--to make things open. These cases, drawn from ethnographic engagement with Open Science debates and semistructured interviews carried out with UK-based biologists and bioinformaticians between 2013 and 2014, show how the enactment of openness reveals judgments about what constitutes a legitimate intellectual contribution, for whom, and with what implications.

Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure

Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell⁻¹) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell⁻¹) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible.

Sustainable funding for biocuration: The Arabidopsis Information Resource (TAIR) as a case study of a subscription-based funding model

Databases and data repositories provide essential functions for the research community by integrating, curating, archiving and otherwise packaging data to facilitate discovery and reuse. Despite their importance, funding for maintenance of these resources is increasingly hard to obtain. Fueled by a desire to find long term, sustainable solutions to database funding, staff from the Arabidopsis Information Resource (TAIR), founded the nonprofit organization, Phoenix Bioinformatics, using TAIR as a test case for user-based funding. Subscription-based funding has been proposed as an alternative to grant funding but its application has been very limited within the nonprofit sector. Our testing of this model indicates that it is a viable option, at least for some databases, and that it is possible to strike a balance that maximizes access while still incentivizing subscriptions. One year after transitioning to subscription support, TAIR is self-sustaining and Phoenix is poised to expand and support additional resources that wish to incorporate user-based funding strategies. Database URL: www.arabidopsis.org.