TechXposure is a database that provides information on the exposure of industries and occupations to 40 digital technologies that emerged over the last decade (2012–2021). The data are available at the 3-digit level for NACE Rev.2 industries and at the 4-digit level for ISCO-08 occupations.
The current version is v0.9.0. For more details on the methodology, see the Working Paper.
Each directory contains a README file describing each file and subdirectory.
DATA FILE | DESCRIPTION |
---|---|
_classification |
Classifications used in the database |
_isco |
ISCO-08 Occupation Exposure |
_nace |
NACE Rev.2 Industry Exposure |
PPLCC_EmploymentImpactEmergingDigitalTechnologies_Oct2024.pdf |
Working Paper |
Please mention the data as the TechXposure
database and cite as:
Prytkova, E., Petit, F., Li, D., Chaturvedi, S., and Ciarli, T. (2024). The Employment Impact of Emerging Digital Technologies. Working Paper.
Citation in bibtex
format:
@techreport{prytkova2024employment,
title={{The Employment Impact of Emerging Digital Technologies}},
author={Prytkova, Ekaterina and Petit, Fabien and Li, Deyu and Chaturvedi, Sugat and Ciarli, Tommaso},
keywords= {{Occupation Exposure, Industry Exposure, Text as Data, Natural Language Processing, Sentence Transformers, Emerging Digital Technologies, Automation, Employment}},
type={{Working Paper}},
year={2024}
}
We greatly appreciate feedback and insights from researchers and policymakers to continually improve the TechXposure
Database. If you have suggestions, questions, or face any issues while using our data, please contact us without hesitation. Your input is vital in enhancing our database and supporting future research. We welcome comments on data accuracy, usability, or desired features. All feedback is valued and will be thoughtfully used to refine the TechXposure
Database for all.
Ekaterina Prytkova (ekaterina.prytkova@univ-cotedazur.fr) & Fabien Petit (f.petit@ucl.ac.uk / fabienpetit.com)
This database is an outcome of PATHWAYS TO INCLUSIVE LABOUR MARKETS (PILLARS). This project received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 101004703.