PARSEC

Apr 12

Written By Ubåt

Building New Tools for Data Sharing and Re-use through a Transnational Investigation of the Socioeconomic Impacts of Protected Areas

Summary

We have two teams in this project with links between: a Synthesis Science team and a Data Science team. Our Synthesis Science team is employing artificial intelligence techniques to analyse satellite images and socio-economic information to better predict and mitigate the effect(s) of actions that potentially threaten the livelihoods and health of local (indigenous) communities. Like most researchers who investigate complex environmental problems, the team depends significantly on the availability of good, spatially dispersed, multidisciplinary, and time-series data.

Our Data Science team of leading environmental data management professionals, data communities (RDA, ESIP), society journals (AGU), and representatives of e-infrastructures for data attribution (e.g., DataCite and ORCID) will develop leading practices on data citation, attribution, credit, and reuse. As part of the integrated work with the synthesis-science team, the data-science team will provide a review of best practices for data management and stewardship using this effort as a case study of the wider scientific community to optimise data access and reuse. The team will also develop and implement a new tool to better track data usage and reuse for researchers.

The project results will be useful to circa 300,000 earth, space, and environmental researchers worldwide. It will advance the momentum of cultural change in the use and reuse of big data in research on real-world problems.

Timeframe of the project

2019 – 2023

Funding source

Belmont Forum as part of its Collaborative Research Action (CRA) on Science-Driven e-Infrastructures Innovation (SEI) for the Enhancement of transnational, interdisciplinary, and transdisciplinary data use in environmental change research.