When using this resource please cite the article for which it was developed: Matysiak, A., Hardy, W. and van der Velde Lucas (2024). Structural Labour Market Change and Gender Inequality in Earnings. Work, Employment and Society, vol. (), pp. - (to be filled in upon publication). The dataset contributes a categorisation of tasks conducted across occupations, with a distinction between social tasks directed "inward" (e.g. towards members of own organisation, co-workers, employees, etc.) and those directed "outward" (e.g. towards students, clients, patients, etc.). This provides more depth to the discussion on technology, labour market changes and gender differences in how these trends are experienced. The dataset builds on the ESCO database v1.0.8 found here. The following task categories are available at occupation levels: Social Social Inward Social Outward Analytical* Routine** Manual * Additionally, a distinction between technical and creative/artistic tasks is provided although it is not used in Matysiak et al. (2024). ** In the initial files, some task items are categorised as Routine, while some are categorised as Non-Routine. In the subsequent steps for occupation-level information, the Routine task score consists of a difference between the Routine score and the Non-Routine score (see the paper for more information). The repository contains four data files at different stages of task development. For the codes, please see the accompanying GitHub repository. The ESCO database covers, i.a., skills/competences and attitudes, to which we jointly refer as task items (as is standard in the literature using other databases such as ONET). For detailed methodology and interpretation see Matysiak et al. (2024). 1) esco_tasks.csv - encompasses all ESCO occupations and all task items with tags on task categorisation into broader categories. It also includes the split between the "essential" and "optional" task items and the variant "management-focused" and "care-focused" measures of social tasks as used in the robustness checks in the Matysiak et al. (2024) paper. 2) esco_onet_tasks.csv - additionally includes pre-prepped task items from the ONET database, traditionally used to describe the task content of occupations. These data can be used to validate the ESCO measures. 3) esco_onet_matysiaketal2024.csv - contains a subset of the variables from esco_onet_tasks.csv used for the Matysiak et al. (2024) paper. 4) tasks_isco08_2018_stdlfs.csv - contains the final task measures after the standardisation and derivation procedures described in Matysiak et al. (2024). For all details on the procedures, applied crosswalks, methods, etc. please refer to the GitHub repository and the Matysiak et al. (2024) paper.