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# * User-agent: * Allow: / # Host Host: https://fairdataihub.org/ # Sitemaps Sitemap: |
Title | Fair Data Innovations |
Description | Making FAIR data practices more FAIR Data Innovations Hub is an organization dedicated to building open source tools that help biomedical researchers understand and follow FAIR Data Principles when showcasing their |
Keywords | fair data, fairhub, fairdataihub, calmi2, calmii, soda, sparc, sparclink, aqua, know more |
WebSite | fairdataihub.org |
Host IP | 76.76.21.21 |
Location | United States |
Site | Rank |
US$1,972,467
Last updated: 2023-05-19 01:37:30
fairdataihub.org has Semrush global rank of 5,366,024. fairdataihub.org has an estimated worth of US$ 1,972,467, based on its estimated Ads revenue. fairdataihub.org receives approximately 227,593 unique visitors each day. Its web server is located in United States, with IP address 76.76.21.21. According to SiteAdvisor, fairdataihub.org is safe to visit. |
Purchase/Sale Value | US$1,972,467 |
Daily Ads Revenue | US$1,821 |
Monthly Ads Revenue | US$54,623 |
Yearly Ads Revenue | US$655,466 |
Daily Unique Visitors | 15,173 |
Note: All traffic and earnings values are estimates. |
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fairdataihub.org. | MX | 3600 | MX Record: 30 alt3.gmr-smtp-in.l.google.com. |
Blog Meet The Team Our Projects SODA for SPARC AI-READI FAIRshare KnowMore SPARClink AQUA Contact Us Open main menu Making FAIR data practices more accessible F indable, A ccessible, I nteroperable, and R eusable (FAIR) data practices are taking the biomedical research world by storm. We build open source tools to help researchers navigate through them. Contact us Our Vision Only with tools that support and assist researchers we will achieve a widespread adoption of FAIR data practices. What are the FAIR Data Principles? The FAIR Data Principles are a set of guidelines for curating and sharing research data such that they are optimaly reusable by both humans and machines. Learn more about FAIR Why are FAIR data practices important? FAIR data practices are crucial for ensuring reproducibility of scientific findings, promoting reuse of data, and enabling AI/ML-driven analysis to ultimately increase the pace of new discoveries. They also ensure proper credits to data generators. What are |
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