Whatâ€™s going to happen to the â€œopen dataâ€ movement in 2015?Â Here are Dennis D. McDonald‘sÂ predictions:
- Some high profile open data web sites are going to die.Â At some sites the lack of updates and lack of use will catch up with them.Â Others will see highly publicized discussions of errors and omissions.Â For some in the industry this will be black eye.Â For others it will be an â€œI told you soâ€ moment causing great soul-searching and a re-emphasis on the need for effective program planning.
- Greater attention paid to cost, governance, and sustainability.Â In parallel with the above there will be more attention paid to open data costs, governance, and program sustainability.Â Partly this will be in response to the issues raised in (1) and partly because the â€œmovementâ€ is maturing.Â As people move beyond the low-hanging-fruit and cherry-picking stage they will be giving more thought to what it takes to manage an open data program effectively.
- Greater emphasis on standards, open source, and APIs. This is another aspect of the natural evolution of the movement. Much of the open data movement has relied on â€œbottom upâ€ innovation and the enthusiasm of a developer community accustomed to operating on the periphery of the tech establishment. Some of this is generational as younger developers move into positions of authority. Some is due to the ease with which data and tools can be obtained and combined by individuals and groups working remotely and collaborating via systems like GitHub.
- More focus on economic impacts of open data in developed and developing countries alike.Â While many open data programs have been justified on the basis of laudable goals such as â€œtransparencyâ€ and â€œcivic engagement,â€ sponsors will inevitably ask questions about â€œimpactâ€ as update costs begin to roll in.Â Some of the most important questions are also the simplest to ask but the hardest to answer, such as, â€œAre the people we hoped would use the data actually using the data?â€ and â€œIs using the data doing any good?â€
- More blurring of the distinctions between public sector and private sector data.Â One of the basic ideas behind making government data â€œopenâ€ is to allow the public and entrepreneurs to use and combine public data with other data in new and useful ways. It is inevitable that private sector data will come into the mix. When public and private data are combined some interesting intellectual property, ownership, and pricing questions will be raised. Managers must be ready to address questions such as, â€œWhy should I have to pay for a product that contains data I paid to collect via my tax dollars?â€
- Inclusion of open data features in mainstream ERP, database, middleware, and CRM products.Â Just as vendors have incorporated social networking and collaboration features with older products, so too will open data features be added to mainstream enterprise products to enable access via file downloads, visualization, and documented APIs. Such features will be justified by the extra utility and engagement they support. Some vendors will incorporate monetization features to make it easier to track and charge for data the new tools expose.
- Continued challenges to open data ROI and impact measurement.Â As those experienced with usage metrics will tell you itâ€™s not just usage thatâ€™s important itâ€™s the impact of usage that really counts. In the coming year this focus on open data impact measurement will continue to grow. I take that as a good sign.Â I also predict that open data impact measurement will continue to be a challenge.Â Just as in the web site world itâ€™s easier to measure pageviews than measure the impacts of the information communicated via the pageviews, so too will it continue to be easier to measure data file downloads and API calls than the impacts the use of the data thus obtained will have.
By Dennis D. McDonald, Ph.D.