UC4 Low carbon energy and energy efficiency policies
Contents
General description of use case
Framing the use case
The section describes the FAIRification work undertaken in the use case "Low carbon energy and energy efficiency policies" of the EERAdata project.
Societal challenges
The FAIR data principles are important for the Findability, Accessibility, Interoperability and Reusability of data. Therefore for efficient use of information and data, it should be accessible to both humans and machines. In this context, machi large-scale survey was particularly helpful in assessing the level of awareness of FAIR data principles in the energy sector community, which also identified the barriers and opportunities of FAIRification process in the y sector and indirectly indicated the relevance of data used to compile them. Therefore, it is necessary to assess the challenges and opportunities raised by the FAIR principles and the conditions to be taken into account to enact them in a responsible manner for the transparent and integrated management of energy data.
Technical challenges
Policies, laws, and regulations play a significant role in catalyzing the transformation of the energy system towards greenhouse gas reduction and energy efficiency, and thus toward climate neutrality. International and national level policies define the space for the application of energy technologies and low carbon energy materials, as well as provide the framework for market activities in general. Therefore currently, a new role for data on low carbon energy and energy efficiency policies is emerging. The need to provide documentation of compliance with regulations is increasing in complexity as integrated monitoring and assessment across fields and economic sectors are rising. In terms of utility documentation should be provided for the entire value chain.
The detailed scope of work in UC4 concerned the following issues:
1.The detailed definition of the current state of application of FAIR/O data principles. In the first step, an extensive review of databases was carried out, resulting in the identification of 30 databases that collect data for 'Low carbon energy and energy efficiency policies' area. Through discussion and research, a choice was made to select COMETS, IEA Policy Database, EUR-Lex and JRC database hub, as databases for further analysis, in context of type and extend of metadata provided, level of implementation of FAIR/O principles, frameworks for metadata used and technical implementation of metadata. Results are available here.
2.Conducting stakeholders awareness survey for the purpose of assessing the current state of knowledge of FAIR data in the area related to policy and strategy. The survey questionnaire was divided into three main parts: questions concerning respondent's awareness of the FAIR data; questions concerning data management, sharing and exchange; questions concerning the use of FAIR data in policymaking, and additional metrics section. The survey was available in the first round until 10 October 2022 and was subsequently extended to 31 October 2022.
Summary of results
The FAIR data principles are important for the Findability, Accessibility, Interoperability and Reusability of data. Therefore for efficient use of information and data, it should be accessible to both humans and machines. In this context, machine-actionability of relevant policy databases from local to global scale is vital for automated tracking, compilation, and inter-comparison with peers. Those arguments directly underline the role played by law regulation and policies in the energy sector and indirectly indicate the relevance of data used to compile them. Therefore, it is necessary to assess the challenges and opportunities raised by the FAIR principles and the conditions to be taken into account to enact them in a responsible manner for the transparent and integrated management of energy data. Policies, laws, and regulations play a significant role in catalyzing the transformation of the energy system towards greenhouse gas reduction and energy efficiency, and thus toward climate neutrality. International and national level policies define the space for the application of energy technologies and low carbon energy materials, as well as provide the framework for market activities in general. Therefore currently, a new role for data on low carbon energy and energy efficiency policies is emerging. The need to provide documentation of compliance with regulations is increasing in complexity as integrated monitoring and assessment across fields and economic sectors are rising. In terms of utility documentation should be provided for the entire supply chain. The above-mentioned issues have become a part of the works carried out under WP7 EERAdata project within which the current state of application of FAIR/O data principles for ‘Use case 4 (UC 4): Low carbon energy and energy efficiency policies’ was assessed. Conducted work allows to assess the level of policy-makers awareness about FAIR data principles and data FAIRification process as well as enable the assessment of commonly used energy databases in terms of meeting FAIR data requirements and standards. A particularly helpful in assessing the level of awareness of FAIR data principles in energy sector community was a large-scale survey, which enabled also identification of the barriers and opportunities of FAIRification process in the area of energy policy sector. An important roles in identifying the significance and impact of data quality in the energy sector policymaking process were played by representatives of various communities and local government units who, using real-life examples, pointed out the consequences and risks of missing data, lack of access to data or misinterpreted data.
Conclusion
The main conclusions resulting from the work carried out under WP 7 are summarized below. Detailed analysis of the policy databases' fulfillment of FAIR/O principles has shown that the problematic issues in the area of ‘reusability‘ resulted directly from deficiencies in the area of ‘interoperability’. Therefore, highlighting the improvement of quality in the area of "interoperability" should also increase quality in the area of "reusability". Focusing the search on practical ways to improve the level of "interoperability" and thus "reusability," it was considered that the starting point should be ontologies from the area of energy policies, which should then be developed, unified and organized. The work focused around workshops involving a wide range of experts, who significantly helped in the ontologies assessment and development. Assessing the level of knowledge of energy sector representatives regarding FAIR data principles and FAIRification process assumption, supported by survey data analysis, pointed to the need to intensify promotional and educational activities to raise awareness about FAIR data's role in the energy ecosystem. Selected research results has shown that (i) policies are a crucial component in the FAIR ecosystem; (ii) policies are not currently structured for machine readability; (iii) some policies are more influential on researchers’ behavior than others; (iv) policies should be aligned with FAIR either explicitly or implicitly. Detailed survey results are available here. Summary of lessons learned. During the EERAdata project under WP 7, a number of analyses were carried out with the main objective of assessing the level of implementation of FAIR principles in databases covering energy-related policies and exploring awareness of the role FAIR plays for energyrelated policies among various stakeholders. Finally, it resulted in the development of specific recommendations for each FAIR data aspects in terms of energy policies are presented below:
F
In the policy-making process, an important issue is the use of reliable and, at the same time, verifiable baseline data. Therefore, an important role in the dataset is played by identifiers that enable fast and error-free identification and reconstruction of the output data.
A
In order to make the policies governing data sharing comparable and able to be unambiguously interpreted by both humans and machines, it is recommended to develop and use a set of common policy elements that are consistently described using a structured markup scheme.
I
FAIR data should be considered as a relevant domain in which various group of stakeholders including policy-makers have an increasingly higher benefit resulting from the availability and interoperability of data allowing, e.g., aggregation and processing of data at different levels of detail depending on the documentation requirements.
R
It is crucial to understand that creation of qualitative metadata assets, as well as proper data management, plays an important role not only for individual organisations/entities, but also represents a valuable resource that can be made available to third parties under certain conditions. Compliance of the data with FAIR criteria, in particular with regard to their ‘reusability’, enables the exchange of datasets with third parties which might enrich further analysis and provide better results/conclusions/services/ overall. The process of data FAIRification is a step towards meeting the needs to improve relevant sharing of secured data and find mutual benefits to collaborate between different actors, representing both the data providers, users and manager. The issue of data security against unauthorised access and the conditions for data sharing, particularly in the area of international cooperation, is a key problem that often prevents the acquisition of data. Therefore, it is necessary to introduce clear systemic solutions for authorised access to the data on different levels of aggregation which would reduce data heterogeneity and thus improve data readability and applicability.
