"Governments have made progress in sharing data openly. We increasingly see governments at all levels developing open data portals and continuing to enhance them with useful information. While they have a large volume of data that can be useful for organizations to build new services or develop new research, there is a much larger opportunity to extract value from data.

Many private sector entities have volumes of data, but may only utilize a small fraction. Significant value could be derived from this information to address challenges facing their organizations and industries. By unlocking access, merging it with other open or proprietary sources of data, and allowing data experts to mine these sources, new insights can be gleaned, leading to better solutions to meaningful problems.

Companies often resist sharing data for a variety of reasons:

    • fears that sharing data will reduce their competitive advantage
    • concerns about re-identification of individuals that could cause privacy problems
    • sharing will diminish or destroy intellectual property rights in the data
    • negative customer/consumer reaction to data sharing



These concerns are valid and need to be considered for any initiatives of this kind. The increasing number of news stories about negative impacts of corporate data sharing demonstrate that the concerns are understandable, and that there is a heightened level of risk in these types of initiatives.

That being said, the challenge isn’t insurmountable. There are safe, secure ways to share data provided a thoughtful, considered approach is taken. By establishing a data sharing policy and setting up a secure platform, it is possible to undertake these types of initiatives while still retaining control over your data and eliminating potential privacy issues. And this can generate a number of significant benefits:

    • ability to tap into the collective strength of the collaborators to identify effective solutions
    • ability for organizations to securely share data with external entities while retaining control of their data assets
    • providing experts with ability to manipulate data within a secure platform to generate insights or solutions
    • potential to generate new industry standards or methodologies that can improve efficiency
    • opportunity to generate positive PR and corporate goodwill within industry and with consumers



A data collaborative program is one mechanism for enabling data sharing. These programs bring together parties from a variety of areas, such as corporate enterprises, startups, not-for-profits, government and academia to collaborate around data with the goal of solving a pre-defined problem. It provides an environment for those who have data to securely share it with those who can use data to develop new insights or build new services. Most often it involves the sharing of multiple datasets that can be combined to create deeper insight or used together to create a solution that could not be developed without the collective data.

There are a number of collaboratives operating around the globe with a goal of generating economic and social benefit through the collective power of their contributors. These range from advancing medical solutions to tackling crime and assisting in disaster relief.


Accelerating Medicines Partnership brings together 12 biopharmaceutical and life science companies, the National Institutes of Health, the U.S. Food and Drug Administration (FDA), and 13 not-for-profit organizations with the goal of reducing the time and cost for developing new diagnostics and therapies for patients. The collaboratives are centred around four diseases: Alzheimer’s, type 2 diabetes, autoimmune disorders of rheumatoid arthritis and lupus, and Parkinson’s disease. The collaborative shares resources and expertise to advance research for new therapies and treatments. The data and analyses derived from the AMP partnership are then shared with the biomedical community to help expedite the creation of treatments.

Global Fishing Watch is a collaborative established between Oceana, an international ocean conservation organization; SkyTruth, experts in using satellite technology to protect the environment; and Google, which provides the tools for processing big data. The mission was to increase transparency of fishing activity to advance ocean sustainability and stewardship. They track activity of large-scale fishing vessels around the world and make the data openly available to allow others to use the information for their own monitoring purposes. The collaborative has grown into a non-profit entity that continues to advance on this mission.

Airbus developed a collaboration service called Skywise that collects and shares data across its supply chain. It provides a method for Airbus and its suppliers to collectively innovate around data sharing and advanced analytics. The service examines data from a number of perspectives to help reduce supply chain disruptions, improving product quality, and improving the efficiency of service maintenance. The end goal is to provide a better end product for customers and generate efficiencies for Airbus and its suppliers that can generate additional economic benefit.

The use of mobile data for the purposes of aiding in disaster relief has been a common thread among data collaboratives. One such example was from the 2015 earthquake that devastated Nepal. NCell, one of the country’s major telecom operators, and Flowminder, a Swedish not-for-profit with expertise analyzing mobile data for natural disaster response, collaborated to examine population movement following the earthquake. By utilizing de-identified data on SIM card movements along with available population data, they were able to examine changes in movements before and after the earthquake. The information, analyzed daily, was able to provide insight on population flow that helped disaster relief teams identify where to direct assistance efforts.

The establishment of data collaboratives can bring many benefits to the parties involved. It can create positive economic change and generate new insights to solve societal problems. And startups or researchers can gain access to larger datasets that can spur evidence-based ideas and solutions. All this leads to continued innovation and can contribute to greater productivity, healthier environments and improved social conditions.


It begins with a will to define a specific problem, identify data sources that can contribute to a solution, and gather the necessary expertise to generate results. The end result is a powerful display of how data can be used to create significant economic and societal improvements."