EDISON Data Science Framework: Part 4. Data Science Professional Profiles (DSPP) Release 4
Creators: name: Demchenko, Yuri
name: Brewer, Steve
name: Wiktorski, Tomasz
Publisher: name: Zenodo
Year: 2022
Subjects: Data Science Professional Profiles (DSPP)
EDISON Data Science Framework (EDSF)
Data Science Data
Scientist Professional
Data Science Curriculum Design

description: This document presents the Data Science Professional Profiles (DSPP) that is important for defining the Data Science organisational roles in the organisation and their alignment with the organizational goals and mission. The Data Science Professional profiles definition is done in the context of the whole EDISON Data Science Framework and is the result of project efforts and wide community contribution.<br> <br> * The proposed Data Science professional profiles are defined as an intended extension to the current ESCO (European Skills, Competences, Qualifications and Occupations) taxonomy and is intended to be proposed for formal inclusion of the new Data Science professions family into the future ESCO taxonomy edition.<br> * The proposed DSPP, when adopted by the community, will have multiple uses. First of all. They will help organisations to plan their staffing for data related functions when migrating to agile data driven organizational model. The Human Resource (HR) departments can effectively use DSPP for vacancy description construction and job candidates assessment.<br> * The definition of the Data Science Professional profiles, together with other EDSF components, will provide a formal basis for Data Science professional certification, organizational and individual skills management and career transferability.<br> <br> When used together with CF-DS, the DSPP can provide a basis for building interactive/web based tools for individual competences benchmarking against selected (or desirable) professional profiles as well as advising practitioners on the (up/re-) skilling path.<br> 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.<br> 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).<br> The EDSF documents are available for public discussion at the EDISON Community initiative at https://github.com/EDISONcommunity/EDSF/wiki/EDSFhome<br>