Creating a Culture of Open Data in Academia Charlotte Day Linked Open Data Professional Development Workshop CABI Wallingford 22nd May 2018

What is open data? Open data does mean different things according to your perspective. I will include a few well-accepted definitions here.

FAIR Data Principles Data should be Findable Data should be Accessible Data should be Interoperable Data should be Re-usable Much data should be open (openly licenced). All data can benefit from being FAIR - clear licence, metadata, persistent, provenance, machine readable http://www.nature.com/articles/sdata201618

5 Star Open Data http://5stardata.info/en/

Open Data and Open Access at PUSH Universities https://f1000research.com/gateways/godan/godan-reports Released June 4, 2018 https://f1000research.com/documents/6-1900

Benefits Provides a public good Enhances and accelerates research and innovation Increases transparency Increases citations and recognition of faculty and their universities Increases potential of identifying research collaborators

Barriers Privacy of research subjects, data security Concerns on misuse of data, IP Funders’ contract requirements Incentives to publish data Lack of resources and capacity to implement donor policy requirements Lack of understanding regarding licensing options and ownership of data

Recommendations Create alignment between funders’ expectations and the research institution’s capabilities Improve faculty’s ability to comply with open access and open data requirements Refine and/or develop open access and open data standards and protocols

Data Wish List Accessible to those who need it Machine-readable High-quality Continuously updated Possess unique identifiers Able to be linked to other data sources Have an open license to reuse the data in any way as long as the original source is credited. These reflect the FAIR Principles!

Donors support data sharing. As funders we intend to promote greater availability and use of data in ways that are: Equitable​ ​- data generated through our funding should where possible be provided to everyone, whilst respecting privacy concerns, in accordance with applicable laws and regulations and crediting the original data source Ethical​ - collectors, users and reusers of data must consider its impact on people and communities, while respecting the ‘FAIR principles’ Engaging​ ​- ensuring that a broad range of people are brought into discussions about what data should be collected, how it should be used, and prioritised for release

FAIR Data Communities Project BMGF Ag Dev grantees, regional implementing partners, and local institutions must be able to: collect high quality data share data reuse other’s data to make better data-driven decisions and create a stronger data sharing community.