Geonet : okt 6, 2021 09:03 PM : Project
As the world has become digitized, sheafs of paper and file drawers have transformed into ephemeral, infinite, and globally accessible databases. The data recorded in information systems—whether generated to comply with regulatory requirements or for specific tasks—has a nominal life cycle of birth; growth; and, finally, obsolescence. While the data never truly dies, it often atrophies in old, unmaintained systems. It is archived and stored for potential reuse later—if anyone remembers where the data is or how the old systems work.
When data is instead accessible, reusable, and open for continuous improvement, it is often of higher quality and has a greater impact on communities. We’ve seen this happen with software over the decades: at first, it was stored on fragile punch cards, and now it is being freely and rapidly shared for reuse and collaboration. This has resulted in undeniably more rapid, complex, and high-quality software innovation.
As Eric Raymond stated in The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary, “given enough eyeballs, all bugs are shallow.” In other words, software code that can be read, used, and fixed by other software engineers will result in better software with fewer problems. And beyond fixing issues with software, making source code available for public access enables it to continually grow and be improved on—which is the case for many key projects that now underpin computer systems around the world.
Open data is experiencing a transformation similar to that of software. Databases that were locked in silos of singular use are now made available and accessible to anyone. This means that people from other departments, municipalities, businesses, and community groups can immediately reuse the data in their own work, providing better context for evaluating complex relationships, making important decisions, and measuring program outcomes. It also means that journalists can use it when researching and reporting on specific issues or trends. And all consumers of the data can provide feedback on data quality issues, possible corrections that need to made, and other potential improvements to the data.