The Data Science Competence Framework (CF-DS) is a cornerstone component of the whole EDISON Data Science Framework (EDSF). CF-DS provides a basis for the Data Science Body of Knowledge (DS-BoK) and Model Curriculum (MC-DC) definitions, and further for the Data Science Professional Profiles definition and certification. The CF-DS incorporates many of the underpinning principles of the European e-Competence Framework (e-CF3.0) that have been used for the Data Science competences definition; in its own turn, this allowed to provide extensions of the new e-CF4.0 version (published as CEN EN 16234-1, 2019) with the Data Science competences. The CF-DS and DSPP have also adopted the classification structure of the European Skills, Competences, Occupations (ESCO) Framework. Corresponding information is provided in the corresponding documents CF-DS and DSPP. This presented Data Science Competence Framework definition is based on the analysis of existing frameworks for Data Science and ICT competences and skills and is supported by the analysis of the demand side (job market) for Data Science professionals in industry and research. The presented CF-DS Release 4 is extended with the skills and knowledge subjects/units related to all competences groups. The document also refined the Data Science workplace) skills definition that includes the Data Science professional skills (Acting and thinking like Data Scientist) and the definition of the general “soft” skills often referred to as 21st Century skills. The current EDSF Part 1 document defines the Data Science Competence Framework and includes the following components: The CF-DS defines five groups of competences for Data Science that include Data Analytics, Data Science Engineering, Domain Knowledge, Data Management and Governance, Research Methods and Project Management for research related occupations, or Business Process Management for business related occupations. The document provides examples of the individual competences mapping to identified skills and knowledge topics for the Data Science Analytics competence group. The identified competences, skills, and knowledge subjects are provided as enumerated lists to allows easy use in applications and provide a basis for developing compatible APIs. The presented CF-DS definition is supported by the corresponding Excel documents and ontology definition that contain a full list of enumerated EDSF attributes. The proposed EDSF, and CF-DS in particular, are intended to provide guidance and a basis for universities and education practitioners to define their Data Science curricula and courses selection, on the one hand, and for companies to better define a set of required competences and skills for their specific industry domain in their search for Data Science talents, on the other hand. The EDISON Data Science Framework (EDSF) includes the following main components: Data Science Competence Framework (CF-DS), Data Science Body of Knowledge (DS-BoK), Data Science Model Curriculum (MC-DS), Data Science Professional Profiles (DSPP), which are extended with new Part 5. EDSF Use cases and applications (EDSF-UCA). The EDSF provides a conceptual basis for the Data Science Profession definition, targeted education and training, professional certification, organizational capacity building, and organisation and individual skills management and career transferability. The initial definition of the EDISON Data Science Framework (EDSF) was done in the Horizon2020 Project EDISON (Grant 675419) that produced Release 1 in 2016 and published Release 2 in 2017. Currently, EDSF is maintained by the EDISON Community initiative that is coordinated by the University of Amsterdam. The new EDSF Release 4 is the product of the wide community of academicians, researchers and practitioners that are practically involved in Data Science and Data Analytics education and training, competences and skills management in organisations, and standardisation in the area of competences, skills, occupations and digital technologies. In particular, the current release incorporates revisions to competences proposed during the Data Stewardship Professional Competence Framework (CF-DSP) definition by the FAIRsFAIR project (Grant 831558).