Abstract
We present a draft Minimum Information About Geospatial Information System (MIAGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The draft MIAGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. The associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data formats plus options for extraction from user-specified JSON formats. We also demonstrate their use in crafting two example depositions of ArcGIS generated maps. We hope this draft MIAGIS standard along with the supporting miagis Python package will assist in establishing a GIS standards group that will develop the draft into a full standard for the wider GIS community as well as a future public repository for GIS datasets.
Original language | English |
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Article number | 389 |
Journal | Scientific data |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s).
Funding
The project described is supported by University of Kentucky Superfund Research Program Grant P42 ES007380 (Pennell) and NSF 2020026 (Moseley). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Environmental Health Sciences nor the National Science Foundation.
Funders | Funder number |
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National Science Foundation Arctic Social Science Program | 2020026 |
National Science Foundation Arctic Social Science Program | |
University of Kentucky | P42 ES007380 |
University of Kentucky |
ASJC Scopus subject areas
- Statistics and Probability
- Information Systems
- Education
- Computer Science Applications
- Statistics, Probability and Uncertainty
- Library and Information Sciences