FAIR Data - Findable, Accessible, Interoperable, and Reusable
Posted: Tue Feb 11, 2025 4:12 am
This awareness has caught on in enterprise data management circles, under names like "Data Fabric" and "Data Mesh." And this has allowed me to make a steady career for the past decade or so working with large organizations (usually banks), helping them to manage their data on a very large scale. I also worked with the EDM Council, a consortium devoted to improving data literacy and practice at an industrial scale, starting with the banks.
But I still have my eye on changing the world — building a network of data that will inform science, medicine, public policy, finance, sustainability, and ending world hunger. But something I learned from doing data management in very large enterprises is that a lot of the issues around data sharing don't have to do with the data itself; they have to do with the services around the data, information about versioning, consistency, delivery, and assurance around the data.
These ideas about data delivery have been summed up very nicely under the acronym FAIR Data Principles, describing how to make data Findable, Accessible, Interoperable, and Reusable.
The FAIR principles have taken the things we learned about effective data management in the enterprise and proposed applying them to data sharing in the world at large.
Dean Allemang - data.world the best FAIR data platform it can be
The FAIR data principles don't prescribe any particular technology, just principles for how to treat your data. When I read them, I felt as though someone had taken all the canada whatsapp number data experience I gained making data re-usable in the enterprise and wrote it out in a few terse lines. Bravo!
But I don't just want to make a practice of FAIR-ifying data, though there are more and more companies who are doing just that — and good on them! I want to make a world where the benefits of FAIR data are so apparent, and the ability to FAIR-ify data becomes so widespread, that it will just be expected that all data will be FAIR.
This is why I joined data.world. Quite simply, while there are a lot of data platforms out there, some based on Semantic Web standards and some not, none of them has the potential to support a vision of a global FAIR data movement as well as data.world. Why do I say this? Here are some reasons:
Anyone can host their data on data.world for free. Yes, for free. You have some interesting data, and you want to share it with the world? Then you should know about data.world. Your account is free, and if you already have an account with Google, Facebook, Twitter, or Github, you don't even need to create a new login. You have a spreadsheet, or a CSV, or some other common data format? Just drop it in. It really is that easy. Go ahead, try it. Click the data.world link, and upload a spreadsheet.
The data on data.world is active right away; that is, you can write and run queries against your data immediately. So that spreadsheet you uploaded just now? Start querying it. It's great that you can download free editions of a lot of databases, install them in your own infrastructure, load data into them and then start querying. With data.world, you’re already querying your data, and you don't have to install anything.
You can share your data and your insights. Those queries you wrote? Those are first-class entities; you can share them with your friends, and even post them as widgets on your website, as I have done with all the exercises in my book.
But I still have my eye on changing the world — building a network of data that will inform science, medicine, public policy, finance, sustainability, and ending world hunger. But something I learned from doing data management in very large enterprises is that a lot of the issues around data sharing don't have to do with the data itself; they have to do with the services around the data, information about versioning, consistency, delivery, and assurance around the data.
These ideas about data delivery have been summed up very nicely under the acronym FAIR Data Principles, describing how to make data Findable, Accessible, Interoperable, and Reusable.
The FAIR principles have taken the things we learned about effective data management in the enterprise and proposed applying them to data sharing in the world at large.
Dean Allemang - data.world the best FAIR data platform it can be
The FAIR data principles don't prescribe any particular technology, just principles for how to treat your data. When I read them, I felt as though someone had taken all the canada whatsapp number data experience I gained making data re-usable in the enterprise and wrote it out in a few terse lines. Bravo!
But I don't just want to make a practice of FAIR-ifying data, though there are more and more companies who are doing just that — and good on them! I want to make a world where the benefits of FAIR data are so apparent, and the ability to FAIR-ify data becomes so widespread, that it will just be expected that all data will be FAIR.
This is why I joined data.world. Quite simply, while there are a lot of data platforms out there, some based on Semantic Web standards and some not, none of them has the potential to support a vision of a global FAIR data movement as well as data.world. Why do I say this? Here are some reasons:
Anyone can host their data on data.world for free. Yes, for free. You have some interesting data, and you want to share it with the world? Then you should know about data.world. Your account is free, and if you already have an account with Google, Facebook, Twitter, or Github, you don't even need to create a new login. You have a spreadsheet, or a CSV, or some other common data format? Just drop it in. It really is that easy. Go ahead, try it. Click the data.world link, and upload a spreadsheet.
The data on data.world is active right away; that is, you can write and run queries against your data immediately. So that spreadsheet you uploaded just now? Start querying it. It's great that you can download free editions of a lot of databases, install them in your own infrastructure, load data into them and then start querying. With data.world, you’re already querying your data, and you don't have to install anything.
You can share your data and your insights. Those queries you wrote? Those are first-class entities; you can share them with your friends, and even post them as widgets on your website, as I have done with all the exercises in my book.