Data should be governed with transparency, inclusivity and accountability due to growing concerns over data protection and digital rights—particularly during the COVID-19 pandemic. Here are four approaches to aligning data values across communities of practice that should be on policymakers’ radars. These draw from a recent Data Values Project webinar, hosted by the Restore Data Rights movement. 

1. Manage expectation gaps. As more players enter the space of data production and digitization, expectations on data governance and sharing will differ. There will likely be conflicting interests in the supply and demand of data—especially around sensitive data and what information can and should be made publicly available. Think, for instance, about the controversies surrounding whether mobile phone-derived data should be used for COVID-19 contact tracing. Ensuring that these expectations are transparently discussed and creating space for inclusively resolving tensions with adequate accountability mechanisms for when things go wrong at the outset reduce suspicions about how and why organizations are collecting and using data. Informing citizens on how their data will be used helps build trust, but we know that informing citizens and even getting informed consent is not enough. Data collectors and controllers must take on greater responsibility to safeguard citizens’ rights through mechanisms that create transparency and promote inclusion, for example, by involving trusted intermediary organizations working at the local level that can help to engage with and solicit input from target communities. 

"Productive collaboration [on data governance] means meeting the needs of governments, being confident to say no to sharing raw data, and respecting the privacy of individuals."  -Sema Sgaier, Surgo Ventures

2. Get the basics right. In Kenya’s journey, establishing systems for data governance meant starting from scratch, and this took time and effort. The Data Protection Act was enacted in 2019, but it took more than a year for an officeholder to be appointed amidst the COVID-19 pandemic. Landmark cases underlined the lack of trust and divided opinions around data protection in Kenya. All these made the process even more difficult and required deliberate efforts to raise awareness: Kenya's government developed manuals, regulations and guidelines and consulted with citizens as part of this process. 

"Data protection is a novel concept for Kenya. Sometimes even public authorities seek guidance on the application of the Data Protection Act." - Rose Mosero, Government of Kenya

For countries with no previous data governance systems, building is also a balancing act between the rights of data subject sand public health amidst the pandemic, between rights and needs of data users and producers and between digitization and data-driven governance efforts and safeguarding data rights. 

3. Evolve statistical systems to retain trust. Since the start of Agenda 2030, there has been unprecedented pressure to deliver more and better statistics and to expand statistical ecosystems to new stakeholders.

The statistical community faces four pressure points including greater demand for granularity in data and for placing data into context and drawing out imprtant patterns (i.e. impacts on the environment, infrastructure, mobility, etc.). Third, there's heightened demand for timely data to enable predictions. And, finally, the number and types of data users and producers have expanded. Along with these pressures, there is additional demand on statistics offices to remain trusted sources of data by putting into place appropriate legal systems to respond. 

"Not many countries in Africa have statistical Acts that suit the digital contexts. If NSOs do not have the right legal systems, it is difficult to protect confidentiality." - Molla Hunegnaw Asmare, UNECA

Sustaining trust in statistics has three dimensions: trust in the quality of data that underpins statistical production, in the integrity of statistics and in the presentation and interpretation of data. Trust also requires safeguards for protecting personal data, investments in data literacy and regular dialogues and communication with citizens.

4. Transition from data governance elitism to a bottom-up approach. The real value of data governance is realized through ensuring that citizens are included in and become part of these conversations and have a say in decisions about their data and digital rights. The data for development community has often been strong advocates of the idealistic view that increasing data collection and usage will lead to social good. But this cannot be achieved at the expense of people and their rights. The value of engaging citizens in establishing core data values and principles and bridging the gap between data optimists and data pessimists is that we can better articulate how to move forward in way that promotes transparency, inclusion and accountability into an advocacy that is more than the sum of its parts. 

These four approaches to align data values across communities of practice demonstrate ways that individuals, institutions and governments can build transparent, inclusive, and accountable data systems and values at a time in which societies are being rapidly shaped by data. We would love to hear from you! Please continue the discussion using #DataValues #RestoreDataRights on social media or by contacting us at datavalues@data4sdgs.org.