The sustainability of the climate is a global problem that requires the involvement of all levels of public governance and the private sector. Energy issues play a crucial role in the Green Deal (GD), and many of these issues are being addressed at the local government (LG) level. The division of competences within the framework of the GD among the European Union (EU), national governments, LGs, and the private sector has not been sufficiently discussed. Existing studies often neglect the specific role of LGs. The aim of this study was to evaluate the extent to which the role of LGs aligns with the core principles of public governance, namely sustainability, solidarity, subsidiarity, and proportionality. The novelty of this study’s methodology lies in the comprehensive and integrated application of all four principles to assess the distribution of competences necessary to achieve global goals. The conclusion of the study demonstrates that, although the functionality and competences of LGs generally comply with these principles, the role of LGs as consultants to and co-legislators with national and EU authorities should be further discussed and expanded. Overall, this study highlights the importance of strengthening the role of LGs as valuable contributors to the governance process.

The contribution of the energy sector to human development (HD) is one of the aspects that requires measuring growth of the overall sustainability of HD. The UN program, Agenda 2030, has defined the vision of advanced development by introducing a sustainable HD paradigm, the balanced integrated development paradigm, in three dimensions: economic, social and environmental. The overall performance of countries is not currently assessed; there are several proposals for measuring sustainable HD level, but none have become widely accepted due to their weaknesses. The selected indirect measurement method reflects the interlinkage of development dimensions in real cases of low data availability. By combining the strengths of existing proposals and eliminating their weaknesses, the measuring methodology has been created and an appropriate tool—the Advanced Human Development Index (AHDI)—has been designed, which ensures unity and concordance of all included comprehensive dimension indices. The calculations confirm the accuracy and simplicity of the measurement. The proposed methodology and AHDI, as a simple, balanced index that is based on result-oriented headline indices, provide the big picture, which will be transparent, acceptable and usable for experts, politicians and the global community to assess the achieved development levels and to make strategic decisions for the coming period.

The paper proposes a new data object-driven approach to data quality evaluation. It consists of three main components: (1) a data object, (2) data quality requirements, and (3) data quality evaluation process. As data quality is of relative nature, the data object and quality requirements are (a) use-case dependent and (b) defined by the user in accordance with his needs. All three components of the presented data quality model are described using graphical Domain Specific Languages (DSLs). In accordance with Model-Driven Architecture (MDA), the data quality model is built in two steps: (1) creating a platform-independent model (PIM), and (2) converting the created PIM into a platform-specific model (PSM). The PIM comprises informal specifications of data quality. The PSM describes the implementation of a data quality model, thus making it executable, enabling data object scanning and detecting data quality defects and anomalies. The proposed approach was applied to open data sets, analysing their quality. At least 3 advantages were highlighted: (1) a graphical data quality model allows the definition of data quality by non-IT and non-data quality experts as the presented diagrams are easy to read, create and modify, (2) the data quality model allows an analysis of "third-party" data without deeper knowledge on how the data were accrued and processed, (3) the quality of the data can be described at least at two levels of abstraction - informally using natural language or formally by including executable artefacts such as SQL statements.

Nowadays, the globally accepted UN concept of sustainable development (SD) is gradually transferred to the city level, including small and medium-sized cities. The implementation of SD settings requires regular measurement of developmental progress to monitor the level achieved in statics and dynamics, and to make strategic decisions for the next period. The existing urban SD indicator systems and indices are not well-suited for the monitoring of specific cities. Benchmarking algorithms and mathematical modelling procedures were applied to create a methodology and mathematical model for measuring the achieved urban SD level and to ensure the most objective selection and proportions of key performance indicators (KPIs) to be included in the model. The model (1) complies with the UN concept, (2) is usable for any EU city, (3) reflects the level of quality of life achieved, and (4) includes a limited number of KPIs related to municipal functionality. Mathematical computation of the (1) causality between the KPIs, (2) selection and proportions of KPIs, and (3) the general level of urban SD, as well as the reasonable combination of universality, accuracy, stability, and simplicity are strong advantages of the model. Using the published mathematical expressions of the model, calculation of the SD level does not require specific skills; the performed stability test also confirms that annual calibration of the model is not necessary. The index will help municipalities in planning and managing SD, and in the rational use of their usually limited resources. As a pilot project, SD level values are calculated for several cities.