New brief from Open Data Watch tackles approaches to sharing public data
Written by Open Data Watch
Data have taken on a new significance in recent years, due to their increased importance for decision making and as a result of the sheer scale at which they are being produced. As quantities of data have increased around the world, calls to make publicly-produced data freely available have also increased. Parallel to this is an increase in the perceived potential of data to solve today’s most pressing challenges. But to realize this potential, the data community must strike a balance between two complementary–but at times contradictory–pillars of openness and privacy.
Our latest brief Maximizing Access to Public Data: Striking the Balance Between “Open by Default” and Targeted Data Sharing, written by Open Data Watch for TReNDS, attempts to address these issues and find a working framework that balances the concerns with data sharing with the public’s right to information. This brief has been produced as part of TReNDS’ work program on public and private data sharing in support of sustainable development.
Open by default
Making data open by default is the preferred policy approach for supporting open data and creates a presumption in favor of openness–i.e. information and data should be shared with the public unless there is a legitimate reason not to. More than 65 countries have committed to this approach and signed up to the Open Data Charter, whose first principle is “Open by Default.”
Though the assumption of open by default applies to the majority of public datasets, there are a number of legitimate exemptions including information and data on national security matters, defense, and international relations, among others. Two areas that are of particular importance are personal information and confidential commercial information. Targeted approaches are needed to assist practitioners and strike the balance between openness and privacy in such areas.
Targeted approaches to data disclosure and sharing
For those seeking to make datasets containing personal or sensitive data as open as possible, techniques range from the fairly crude–removing sensitive data from datasets and redacting documents–to the more complex, such as using de-identification techniques that can be automated.
In addition to protecting privacy and sensitive data, the balance between openness and commercial confidentiality must be struck, too. The sharing of public data with private entities for the purpose of the performance of a public function must be based on mutual trust. There must be trust on the part of administrative authorities that private corporations will not misuse public data and put individuals or national interests at risk, and trust on the part of private companies that their commercial interests will not be undermined through the disclosure and sharing of any confidential material.
Finding balance
The brief that accompanies this blog emphasizes striking a balance, providing the groundwork and foundations for how publicly produced data can be safely and responsibly shared to help achieve development outcomes and contribute to evidence-informed decision-making. As the amounts of data in the world are growing, so is our community’s research in this space around public-private data collaboration. But more is needed to unlock valuable datasets to unlock the keys to the world's most difficult problems. A number of areas stand out as being relevant to practitioners working in the data for development field:
A serious issue that merits further exploration is what options for responsible public data sharing exist in countries and contexts where data protection, privacy, and access to information laws are weak or non-existent. What types of alternative mechanisms, if any, can be used to safely and responsibly share data between stakeholders? What is the role of good data management and governance in such situations?
As data production increases over time and the role of the private sector becomes more critical to achieve the SDGs and other development outcomes, what are the opportunities and risks involved in private-to-public and private-to-private data sharing in the development sector?
And lastly, the data revolution has given rise to new forms of public-private partnership that have never existed at scale before. These new types of partnership will require new frameworks, mechanisms, and contracts to enable responsible and safe data sharing. What do these look like? And who will be responsible for overseeing them?
Read more in Maximizing Access to Public Data: Striking the Balance Between “Open by Default” and Targeted Data Sharing and about other data sharing initiatives and research here.