{"id":1548702,"date":"2025-07-15T08:11:30","date_gmt":"2025-07-15T15:11:30","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1548702"},"modified":"2025-08-11T06:19:53","modified_gmt":"2025-08-11T13:19:53","slug":"help-to-make-your-data-fair-part-1","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis\/sharing-collaboration\/help-to-make-your-data-fair-part-1","title":{"rendered":"Help to make your data FAIR"},"author":9522,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23851,37511],"tags":[27771,639141,761302,521342],"industry":[],"product":[421922],"class_list":["post-1548702","blog","type-blog","status-publish","format-standard","hentry","category-data-management","category-sharing-collaboration","tag-metadata","tag-open-platform","tag-open-standards","tag-sdi","product-arcgis"],"acf":{"short_description":"How the ArcGIS system supports your implementation of the FAIR data principles - findable, accessible, interoperable, and reusable.","flexible_content":[{"acf_fc_layout":"content","content":"

This article provides an overview of the FAIR data principles and looks at how ArcGIS supports geospatial data providers in making your data FAIR.<\/p>\n

Understanding FAIR<\/h1>\n

We all need and benefit from easy access to interoperable data for decision-making. The FAIR data principles were published in Nature Scientific Data1<\/a><\/sup>\u00a0in the spirit of improved data management among researchers who increasingly depend on data that are easily F<\/span>indable<\/strong>, A<\/span>ccessible<\/strong>, I<\/span>nteroperable<\/strong>, and R<\/span>eusable<\/strong> (FAIR). Beyond researchers, it turns out that these same principles are of universal value to a broad range of data managers and users.<\/p>\n

The spirit of FAIR is to improve the discoverability of interoperable datasets. If a person or a machine\/agent does not know about a dataset, how would we ever find, connect to, and reuse it?<\/p>\n

Open data<\/h2>\n

It is important to note that FAIR data is not the same as open data; these are complementary concepts. As explained by Maastricht University,2<\/a><\/sup>\u00a0open data is data that can be freely used, shared, and built on by anyone. The FAIR principles provide a set of best practices for sharing data in ways that can respect any ethical, legal, or contractual restrictions. They do not state that data must be free of charge or unencumbered by license conditions. Instead, the FAIR principles focus on the future interoperability of data and infrastructure, within which data sources are properly documented and accessible. Between the lines, FAIR helps providers understand that shared data need a bit of care to be truly useful.<\/p>\n

The principles refer to three types of entities: data<\/strong> (or any digital object), metadata<\/strong> (information describing the data), and infrastructure<\/strong> (tools and systems). The FAIR principles are further broken down into sub-prnciples elaborated in the appendix below. For instance, principle F4 defines that both metadata and data are registered or indexed in a searchable resource: the infrastructure component.<\/p>\n

The GO FAIR initiative3<\/a><\/sup>\u00a0recently provided a handy annotated version to understand the FAIR Principles<\/a> more thoroughly. According to GO FAIR, the vision is to foster the coherent development of the global Internet of FAIR Data & Services (IFDS), focusing on early outcomes in the European Open Science Cloud (EOSC).4<\/a><\/sup>\u00a0See also the European Cloud Initiative – Building a competitive data and knowledge economy in Europe.5<\/a><\/sup>\u00a0But of course, the FAIR principles are of general interest worldwide!<\/p>\n

The four FAIR principles are as follows:<\/h2>\n

Findable<\/strong>\u00a0data are the first step to reusable data. Machine-readable data and metadata, combined with search engine optimization (SEO) techniques, help make your data findable by web search engines like Google and explorable by humans.<\/p>\n

Accessible<\/strong>\u00a0data lets users know how to access the data they find, possibly including authentication and authorization. Accessible can apply to open public data and private and secure data available only to authorized users.<\/p>\n

Interoperable\u00a0<\/strong>data can be integrated with other data and systems, leveraging open standards and specifications.<\/p>\n

Reusable <\/strong>data are richly described by metadata,\u00a0released with a transparent data usage license, and adhere to domain-relevant community standards. Reusability is a primary goal of the FAIR data principles.<\/p>\n

Industry adoption of FAIR<\/h1>\n

The geospatial community has embraced the FAIR data principles and has long appreciated the need for accessible and interoperable data. In 2021, the Open Geospatial Consortium<\/a> (OGC) standards development organization updated its mission statement, embracing these principles: “The organization represents over 500 businesses, government agencies, research organizations, and universities united with a desire to make location information FAIR \u2013 Findable, Accessible, Interoperable, and Reusable.”<\/p>\n

As a principal member of the OGC, Esri is united in supporting this vital mission. So, what does it mean in concrete terms for Esri to support the FAIR data principles? Ultimately, it is about helping you, our users who produce, publish, collaborate, share, and (re)use the world\u2019s location-based data. Our goal is to ensure that the ArcGIS system enables FAIR data with appropriate geospatial infrastructure.<\/p>\n

Esri has a history of supporting the spirit of the FAIR principles:<\/p>\n