A Global Data Ecosystem for Agriculture and Food

Agriculture would benefit hugely from a common data ecosystem. Produced and used by diverse stakeholders, from smallholders to multinational conglomerates, a shared global data space would help build the infrastructures that will propel the industry forward. In light of growing concern that there was no single entity that could make the industry-wide change needed to acquire and manage the necessary data, this paper was commissioned by Syngenta with GODAN’s assistance to catalyse consensus around what form a global data ecosystem might take, how it could bring value to key players, what cultural changes might be needed to make it a reality and finally what technology might be needed to support it. This paper looks at the challenges and principles that must be addressed in in building a global data ecosystem for agriculture. These begin with building incentives and trust: amongst both data providers and consumers: in sharing, opening and using data. Key to achieving this will be developing a broad awareness of, and making efforts to improve, data quality, provenance, timeliness and accessibility. We set out the key global standards and data publishing principles that can be followed in supporting this, including the ‘Five stars of open data’ and the ‘FAIR principles’ and offer several recommendations for stakeholders in the industry to follow

Open data leaders network digest

While this digest focuses on challenges for civil servants, many of the techniques and lessons discussed apply to open data leaders in private or third-sector organisations. The digest represents a collection of reflections from leaders of open data initiatives about their experience in driving change, with insights about enabling governance reform, working in coalition, tackling implementation challenges, and stimulating innovative uses of data. In some ways, civil servants who innovate with data are performing the tasks of entrepreneurs. The Open Data Institute (ODI) connects, equips and inspires people around the world to innovate with data.World BankUnited Kingdom’s Department for International Development (DFID)Global Affairs Canada (GAC

City Open Data Policies

The capture and analysis of data is transforming the 21st Century. As society becomes more data driven, data has the ability to drive the bottom line for private companies and help the public sector to define where and how services can best be delivered. In City Open Data Policies: Learning by Doing, the National League of Cities identifies how cities can take advantage of the opportunities presented by open data initiatives.SUMMARY OF RECOMMENDATIONSLeadership: Political support stands out as one of the key requirements to implementing a successful open data project.Appropriate Legislation: Enacting legislation or formal policies is a crucial step toward ensuring the growth and sustainability of open data portals. Funding: Open data initiatives do not require high levels of funding. It is, however, important that the programs have their own budget line items where resources are specifically allocated. Technical Approach: Leading U.S. cities rely on commercial platforms that facilitate the implementation of open data initiatives, provide technical expertise, and ensure 24/7 customer support, often at a lower cost than providing these services in-house. Stakeholder Involvement: Open data is a two-way process. It is, therefore, essential to encourage participation and engagement among multiple stakeholders including: community members; non-profits; universities; the press; businesses; city departments; and other levels of government. Many cities adopt a flexible, and usually informal, approach to interact with the stakeholders. Measuring Success: Developing evaluation tools should be an integral part of any future open data policies

Data capacity building in the global south : emergent patterns and insights from 24 IDRC data for development (D4D) projects

Strengthening data capacity across civil society, governments, and the private sector in the global south has been an important target outcome of IDRC's Theory of Change for Open Data for Development (OD4D). This study reflects a full review and synthesis of 24 projects related to data capacity building that were undertaken for the purpose of identifying common themes (patterns), effectiveness criteria, and program design considerations. The goal is to determine keys for success, longer-term impact, and expanded knowledge sharing/re-use

International open data conference 2016 : summary report and the second action plan for international collaboration

Supported by an online archive of more than 80 sessions and 20 special events (Madrid, 2016), this report reflects on the discussions and debates that took place at the IODC, as well as information shared on a wide range of global initiatives. The International Open Data Conference (IODC) brings together the international open data community to discuss key trends and issues that are shaping the future of open data. Data needs to be reusable, but more importantly, actually used. The overarching focus is on strengthening the relevance of specific data released to address specific problems.World BankUnited Kingdom’s Department for International Development (DFID)Global Affairs Canada (GAC)

Exposing WikiPathways as Linked Open Data

Biology has become a data intensive science. Discovery of new biological facts increasingly relies on the ability to find and match appropriate biological data. For instance for functional annotation of genes of interest or for identification of pathways affected by over-expressed genes. Functional and pathway information about genes and proteins is typically distributed over a variety of databases and the literature.

Pathways are a convenient, easy to interpret way to describe known biological interactions. WikiPathways provides community curated pathways. WikiPathways users integrate their knowledge with facts from the literature and biological databases. The curated pathway is then reviewed and possibly corrected or enriched. Different tools (e.g. Pathvisio and Cytoscape) support the integration of WikiPathways-knowledge for additional tasks, such as the integration with personal data sets. 

Data from WikiPathways is increasingly also used for advanced analysis where it is integrated or compared with other data, Currently, integration with data from different biological sources is mostly done manually. This can be a very time consuming task because the curator often first needs to find the available resources, needs to learn about their specific content and qualities and often spends a lot of time to technically combine the two. 

Semantic web and Linked Data technologies eliminate the barriers between database silos by relying on a set of standards and best practices for representing and describing data. The architecture of the semantic web relies on the architecture of the web itself for integrating and mapping universal resource identifiers (URI), coupled with basic inference mechanisms to enable matching concepts and properties across data sources. Semantic Web and Linked Data technologies are increasingly being successfully applied as integration engines for linking biological elements. 

Exposing WikiPathways content as Linked Open Data to the Semantic Web, enables rapid, semi-automated integration with a the growing amount of biological resources available from the linked open data cloud, it also allows really fast queries of WikiPathways itself. 

We have harmonised WikiPathways content according to a selected set of vocabularies (Biopax, CHEMBL, etc), common to resources already available as Linked Open Data. 
WikiPathways content is now available as Linked Open Data for dynamic querying through a SPARQL endpoint: http://semantics.bigcat.unimaas.nl:8000/sparql

Open data and Earth observations

Abstract Earth observations (EO) represent a growing and valuable resource for many scientific, research and practical applications carried out by users around the world. Access to EO data for some applications or activities, like climate change research or emergency response activities, becomes indispensable for their success. However, often EO data or products made of them are (or are claimed to be) subject to intellectual property law protection and are licensed under specific conditions regarding access and use. Restrictive conditions on data use can be prohibitive for further work with the data. Global Earth Observation System of Systems (GEOSS) is an initiative led by the Group on Earth Observations (GEO) with the aim to provide coordinated, comprehensive, and sustained EO and information for making informed decisions in various areas beneficial to societies, their functioning and development. It seeks to share data with users world-wide with the fewest possible restrictions on their use by implementing GEOSS Data Sharing Principles adopted by GEO. The Principles proclaim full and open exchange of data shared within GEOSS, while recognizing relevant international instruments and national policies and legislation through which restrictions on the use of data may be imposed. The proposed paper focuses on the issue of the legal-interoperability of data that are shared with varying restrictions on use with the aim to explore the options of making data interoperable. The paper analyses legal protection regimes and their norms applicable to EO data. Based on the findings, it highlights the existing public law statutory, regulatory, and policy approaches, as well as private law instruments, such as waivers, licenses and contracts, that may be used to place the datasets in the public domain, or otherwise make them publicly available for use and re-use without restrictions. It uses GEOSS and the particular characteristics of it as a system to identify the ways to reconcile the vast possibilities it provides through sharing of data from various sources and jurisdictions on the one hand, and the restrictions on the use of the shared resources on the other. On a more general level the paper seeks to draw attention to the obstacles and potential regulatory solutions for sharing factual or research data for the purposes that go beyond research and education

Making open data work for plant scientists

Despite the clear demand for open data sharing, its implementation within plant science is still limited. This is, at least in part, because open data-sharing raises several unanswered questions and challenges to current research practices. In this commentary, some of the challenges encountered by plant researchers at the bench when generating, interpreting, and attempting to disseminate their data have been highlighted. The difficulties involved in sharing sequencing, transcriptomics, proteomics, and metabolomics data are reviewed. The benefits and drawbacks of three data-sharing venues currently available to plant scientists are identified and assessed: (i) journal publication; (ii) university repositories; and (iii) community and project-specific databases. It is concluded that community and project-specific databases are the most useful to researchers interested in effective data sharing, since these databases are explicitly created to meet the researchers’ needs, support extensive curation, and embody a heightened awareness of what it takes to make data reuseable by others. Such bottom-up and community-driven approaches need to be valued by the research community, supported by publishers, and provided with long-term sustainable support by funding bodies and government. At the same time, these databases need to be linked to generic databases where possible, in order to be discoverable to the majority of researchers and thus promote effective and efficient data sharing. As we look forward to a future that embraces open access to data and publications, it is essential that data policies, data curation, data integration, data infrastructure, and data funding are linked together so as to foster data access and research productivity

ATLAS open data project: HEP for everyone

We explore the many ways that public High Energy Physics resources are employed to teach and outreach particle physics and computer science. The current ATLAS model of Open Access to recorded and simulated data offers the opportunity to access datasets with a focus on education, training and outreach. This mandate supports the creation of platforms, projects, software, and educational products used all over the planet. We describe the overall status of ATLAS Open Data http://opendata.atlas.cern activities, from core ATLAS activities and releases to individual and group efforts, as well as educational programs, and final web or software-based (and hard-copy) products that have been produced or are under development. The relatively large number of heterogeneous use cases currently documented is driving an upcoming release of more data and resources for the ATLAS Community and anyone interested to explore the world of experimental particle physics and the computer sciences through data analysis