This week marks the launch of the first-ever UN World Data Forum, aimed at bringing together data experts and sustainable development leaders. Danny Lämmerhirt shares findings from a new research series on citizen-generated data, how it can be used to monitor and drive change for sustainable development, and why this matters for civil society.
Image credit: Aotora (CC BY)
With the advent of the 2030 Agenda for Sustainable Development and evaluation of progress around the Sustainable Development Goals (SDGs), actions around sustainability have increasingly centred around data collection, monitoring, and key indicators. The United Nations called for a data revolution – tapping into the vast trove of existing and emerging data sources – in order to prevent the marginalised and most vulnerable from being hidden behind national average numbers.
This is a major step forward to promote concerted efforts around sustainability on an international stage. It acknowledges the role of information to change the way we live. But it leaves the questions open on how nation-wide monitoring can be translated into local action. How can the data revolution drive progress around sustainability? Will it foreground the issues that matter to the most vulnerable and marginalised?
The role of data for sustainable development
Data is not only a mere camera to look unto the world. By determining what is measured and how, data writes a certain story–and leaves out many others that could be written. Citizens and civil society increasingly recognise the value that data holds in tackling the issues affecting our lives – whether they are collecting evidence on oil spills in the Gulf of Mexico, running surveys to understand the satisfaction of local communities with health facilities, or challenging existing statistics about politicised topics.
“Citizens and civil society increasingly recognise the value that data holds to tackle the issues affecting our lives…”
These projects prove the need for, what Jonathan Gray calls, a democratised data revolution – enabling citizens to ‘read’ and understand governance issues, providing them with evidence to engage with politics, or sparking their imagination to design and implement a solution to a problem.
Research series on Citizen-Generated Data can be found here.
This blogpost seeks to broaden our imagination of the role of data for sustainable development and provoke thinking on how to democratise the data revolution. Open Knowledge International teamed up with the DataShift to understand how citizens and civil society can create their own data to foreground the problems that matter most to them, and to directly monitor, demand or drive change on issues affecting them.
The series discusses three topics: Our first research piece sheds light on the incentives to produce citizen-generated data. The second research piece dives into the question how citizens generate data to inform decision-making and drive sustainability. If and how citizen data can be linked to the Sustainable Development Goals was subject of research piece three.
What follows is a list of ten provocations for a sustainability agenda that reflects the needs of civil society inspired by our research.
10 Critical Insights for Democratising the Data Revolution
1. Data needs to resonate with human problems, perceptions, and knowledge, to drive sustainability
In order to progress sustainability, support decision-making, and trigger action, the problems facing different stakeholders need to be well understood. Stakeholders have different priorities, values, or responsibilities, and are affected differently by an issue. Some actors may lack the literacy, knowledge, time, or interest to engage with complicated data.
Civic initiatives are most successful if they understand these nuances, and translate their data into digestible, easily understandable, and relevant messages. We observed that citizen-generated data transports the issue into other people’s minds by using a common framing, a narrative, or a story that resonates with other people’s priorities. Some case studies showed that the SDGs can be a useful common framing for collaboration between citizens, civil society, government, and the private sector – enabling buy-in from decision-makers, funding, or other support for the cause of a civic project.
2. We must be more sensitive to figuring out which types of information is most useful for different types of decision-making
Of paramount importance are questions around what type of information is most useful and for whom. National government bodies may be responsible for allocating money to regions for water-point construction. Responsibility for their maintenance may reside with local districts. While the national government needs comparative data across regions to allocate infrastructure investments, local districts need hyperlocal water-point information.
The main purpose of the SDGs is to advance progress on sustainable development, which first and foremost requires action. However, the main focus lies on how to monitor actions on a national scale. A democratised data revolution would be more sensitive towards the data needed to enhance action at different geographic scales – but particularly on a local scale, in the realm of the everyday, where sustainable actions eventually have to be enrolled. It would start with the question which collaborations and governance arrangements are required to tackle which kinds of problems, and what data is needed to do so.
3. A democratised data revolution understands the vast array of actions needed to drive sustainability.
Citizen-generated data can inform diverse types of human decision-making that go beyond monitoring. Besides agenda setting and the flagging of problems, citizen-generated data can inspire citizens to design their own solutions. It can also give citizens the literacy to ‘read’ and understand governance issues and thereby provide confidence to engage with politics. Sometimes data can be used to directly implement a solution to a problem.
Citizen-generated data can directly steer behaviour and enable better actions by giving stakeholders relevant information to enable actions. It can also help taking decisions, or rewarding certain actions as performance indicators do. The value of citizen-generated data is fairly broad and depends largely on the issue it is used for and the individuals, groups, organisations, and networks using it.
4. National Statistics Offices are important for national monitoring – but actual action towards sustainable development is borne on the shoulders of strong collaborations between governments, civil society, and others.
Given the holistic nature of sustainable development, achieving the SDGs requires concerted efforts. Projects working with citizen-generated data are exemplary for cross-sectoral collaborations. They often bring together actors from government, the private sector, and civil society, all of which have very different interests in the same data. Different actors can value different aspects of the data; understanding how actors perceive this value is key to build multi-stakeholder partnerships.
The right degree of participation is essential to manage collaborations: Should citizens or policy-makers be engaged in the definition of data? How does this affect the credibility of data and buy-in? Who should be engaged in the dissemination of findings? Does the project benefit collaborate with a ‘knowledge broker’ like an experienced advocacy group, a university, or a newspaper?
5. A democratised data revolution has a user-centric vision of data quality.
The SDGs argue that data needs to be accurate, reliable, disaggregated, and timely to be useable for SDG monitoring. Often citizen-generated data is refuted as lacking representativity and accuracy, or as not meeting other features of ‘good quality data’. This is only partly true: In practice, data is of ‘good quality’ if it is fit for purpose. If data shall drive action on the ground it often needs to match with the action at hand. Long-term monitoring needs reliable, accurate, and standardised data.
Setting the agenda for a formerly unknown issue may require a citizen-generated data project to build trust, and to ensure credibility. Some projects might need to produce highly disaggregated data, other tasks only require rough indications of trends. Successful citizen-generated data projects embrace these nuances instead of refuting data. It does not mean that methodological rigour is irrelevant for citizen-generated data. The opposite is the case. Data should be thoughtfully designed in order to address specific tasks and to respond to more ‘human criteria’ of data quality like issues of trust. What matters is that citizens collect data in a systematic way that demonstrates how the data was collected, and processed in the first place.
6. A democratised data revolution embraces the value of ‘soft data’.
Different types of data have different usefulness. The term ‘data’ itself seems to suggest a very narrow notion of numbers, figures, and statistics. Actors involved in policy-making seem to prefer ‘hard’ evidence (e.g. quantitative data from researchers and government agencies) over ‘soft’ evidence (e.g. narrative texts, personal perceptions, or autobiographical material). The soft evidence is often neglected, in favour of numbers which become a main argumentative device. Debates around the data revolution or sustainable development data should not gloss over the fact that narrative texts, individual perceptions, interviews, images or video footage all count as ‘data’ – which might be best understood broadly as a building block of human knowledge, decision-making, and action.
In observed case studies, we found that soft data residing in written reports sparked investigations, guided civil society to spot the facts in official government documents and flag issues. In other cases, personal perceptions gave contextual information on why high-level policies succeeded or failed. A fixation on numbers is likely to hamper the quality of policy-making. Soft evidence, such as personal qualitative stories (including from marginalised groups), should, therefore, be more readily considered in policy decisions.
7. Passive monitoring, analysing, and visualising will not help to tackle sustainable development – targeted engagement strategies are needed.
Targeted engagement strategies do not end with publishing reports or visualising data online. Instead, the engagement methods need to be suitable for individual stakeholders and often involve public hearings, educational meetings with local decision-makers, on-site visits with decision makers, hackathons, or others. The engagement strategies should fit with the desired change, be it to change policies, perceptions, or individual behaviour.
8. Citizen-generated data provides contextual information around an SDG indicator and can prevent silo thinking
Given, that a fair amount of citizen-generated data projects is grounded in sub-national contexts, it can provide a baseline to understand (the absence of) progress around the SDGs. For instance, citizen-generated data projects working on disaster risk reduction may conduct hazard risk mapping, indicating local vulnerabilities to environmental disaster. The maps can be a baseline used to understand the outcomes of natural disasters. In other cases, citizens can collect data that is relevant across SDGs. In this way, citizen-generated data can contribute to preventing silo-thinking. For instance, data on land acquisition may be usable to understand gender-disaggregated land ownership, as well as the amount of arable land.
9. A democratised data revolution needs trust and credibility if it is to leverage the voices of the marginalised
Emerging data sources and practices put into question the monopoly of established data producers and routines. Big data, small data, citizen science, or social media are all examples of a reconfiguration how data becomes trustworthy information. Citizen-generated data can be leveraged to build trust with different communities, but a lack of official recognition or credibility can hamper uptake. What is needed is a culture of openness among governments, high-level decision-makers, and others towards emerging data sources that are not administered by established data producers.
10. The politics of data are crucial – a democratised data revolution acknowledges that some data does not represent sterile facts, but matters of concern.
The very process of creating data is born out of priorities over what to measure and how. The same applies to citizen-generated data which is intended to be a direct reflection of citizen’s issues. Sometimes citizens might want to highlight the magnitude of a problem and scale their data production across local regions. In order to scale citizen-generated data projects, collective data standards can be developed to render citizen-generated data comparable – sometimes at the expense of evening out local differences between data. A democratised data revolution would be more attuned to the political processes behind standardisation and would embrace the fact that sustainable development will not solely be built on one-size-fits-all solutions.
You can find all three reports on Citizen-Generated Data on the DataShift website.
Danny Lämmerhirt works on the politics of data, sociology of quantification, metrics and policy, data ethnography, collaborative data, data governance, as well as data activism. You can follow his work on Twitter at @danlammerhirt. He was research coordinator at Open Knowledge Foundation.