An analysis of the FAIRness of water related datasets on the Government of Canada’s “Open Maps” platform

被引:0
|
作者
McGrath H. [1 ]
Harrison A. [1 ]
Salisbury L. [1 ]
Denny S. [1 ]
Fuss C. [1 ]
机构
[1] Canada Centre for Mapping and Earth Observation, Natural Resources Canada, Ottawa
关键词
FAIR; Open data; Water classification; Web data portal;
D O I
10.1139/geomat-2020-0021
中图分类号
学科分类号
摘要
The Canada Centre for Mapping and Earth Observation (CCMEO) branch of Natural Resources Canada is supporting geographic analysis and evidence-based decision making by delivering core geospatial data that are accurate, dynamic, authoritative, and accessible. One role of CCMEO is in the dissemination of spatial datasets to Canadian citizens and the broader public. Over time, the volume of data, contributors, file formats, types, and frequency of data updates has increased. CCMEO is working diligently to ensure that the datasets it provides are findable, accessible, interoperable, and reusable (FAIR) to support the Government of Canada’s commitment to “openness and expansion of data resources”. In this study, we undertake an environmental scan of the Government of Canada collection of geospatial datasets related to the theme of “water” to evaluate how FAIR the data are and assess how close the available geospatial data are to meeting the federal government’s stated commitment. The data were tested with the online FAIR self-assessment tool SATIFYD from Data Archiving and Networked Services (DANS). The computed average over the collection is 70% (or 3.5/5) with datasets from Statistics Canada achieving the highest average rating. Key areas to improve the FAIR score include adding a globally unique and persistent identifier, domain standardized vocabulary (where possible), improving the metadata by adding provenance information and data or workflow process descriptions, linked data, and citation information. Other considerations to improve the ability to identify relevant search results include a new hierarchical categorization scheme and an improved method to filter results per a feature-based location search. © 2021, Canadian Science Publishing. All rights reserved.
引用
收藏
页码:65 / 76
页数:11
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