The goal of the WG is to reduce data management overhead within and between organisations working with wind energy. This will be done by firstly creating a recommendation “Guidelines for improving FAIR data maturity in wind energy in practice”. This will then be used to create a wind energy FAIR Implementation Profile (FIP)1 , which is a methodology developed within the GO FAIR initiative. FIP will give the scientific and research communities the opportunity to express their choices of standards, technologies, tools and procedures by which they fulfil the FAIR principles.

The goal of the WG is to reduce data management overhead within and between organisations working with wind energy. This will be done by firstly creating a recommendation “Guidelines for improving FAIR data maturity in wind energy in practice”. This will then be used to create a wind energy FAIR Implementation Profile (FIP)1 , which is a methodology developed within the GO FAIR initiative. FIP will give the scientific and research communities the opportunity to express their choices of standards, technologies, tools and procedures by which they fulfil the FAIR principles.

We will achieve these goals by first reviewing and evaluating the current data sharing and publishing landscape in wind energy. This landscaping step will be based on a review paper we recently wrote about knowledge engineering in wind energy [1], but will extend the review of semantic artefacts to data sharing and publishing in general. For example, we will verify to which degree these artefacts can be described using the available controlled vocabularies. This includes, for example the WEAVE and NEAT controlled vocabularies, as well as the Task 43 WRA Data Model [1]. We will also will apply the “FAIR Data Maturity Model” [2] and the “Guidelines for publishing structured metadata on the Web” [3] to a choice of existing open data sets as well as data with access restrictions provided to WG members by commercial organisations such as wind farm owner/operators or service providers or governmental organisations (maintaining confidentiality). The choice of datasets will be made by taking a range of different data sets across the wind energy project lifecycle at different FAIRness levels based on the results of the above-mentioned review.