Using and Improving Data
What is it?
Data are simply information, facts or evidence about something that can be used in calculating, analysing, reasoning or planning. Data may be quantitative (i.e. information that is conveyed by numbers) or qualitative (i.e. information that is conveyed by descriptive language.) Data may also be official or non-official. Official data are generally produced by National Statistical Offices (NSOs) and include data gathered from formal government processes such as censuses or household surveys. Ideally, all official data should be ‘open data’ meaning that they are freely available for everyone to access, use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control.1
Non-official data are data that are produced by non-governmental actors such as research institutions, academia, the private sector, CSOs or citizens themselves.2 ‘Citizen-generated data’ are defined by the DataShift initiative as “data that people or their organisations produce to directly monitor, demand or drive change on issues that affect them.”3 This data may be generated through research, social audits, crowd-sourcing online platforms, mobile phone and SMS surveys, phone calls, reports, storytelling, social media and community radio.4
Why is it important?
The 2030 Agenda recognizes that quality, accessible, timely and reliable disaggregated data are essential to measure progress on the SDGs and to ensure that no one is left behind.5 In relation to accountability, data are critical to monitor progress on the SDGs, ensuring that citizens know what their government is doing and are able to assess whether it is working. Data on the situation of vulnerable or marginalized groups are particularly critical in order to determine whether governments are fulfilling the pledges to leave no one behind and to reach the furthest behind first. Holding data is power and access to data can open the door to conversations with policy makers, allowing CSOs and citizens alike to validate, challenge or identify gaps in official narratives of SDG progress. Where official data on the SDGs are generated in a participatory manner, they can empower citizens and support a people-centred approach to accountability by ensuring that citizens themselves are engaged in reporting and providing rationale for SDG progress.
Non-official data – including citizen-generated data – are especially important for accountability as they can offer a more complex and accurate picture of progress at all levels. Such data can complement official sources of data, fill gaps in data and/or supplement official reporting when the quality, availability or impartiality of official data is insufficient.6 The use of non-official data from different sources can also help to build trust and credibility among citizens regarding the accuracy of official monitoring and reporting on SDG progress.7 Further, non-official data can help to ensure that people’s perspectives and experiences – including communities or population groups that may be overlooked by official data collection processes – are documented and taken into account in SDG implementation and follow-up and review processes.8 Although the 2030 Agenda does not explicitly recognize the role of non-official data, the UN General Assembly has adopted a resolution that “recommends that national statistical systems explore ways to integrate new data sources into their systems to satisfy new data needs of the 2030 Agenda.”9Non-official data should be considered as valid and credible as official data if their methodologies are as robust and open to public scrutiny as those used to produce official data.10
How can it be used?
There are many ways that CSOs can engage with data to promote accountability for the SDGs, including the following:
1. Advocate for official data to be open – As an initial step, CSOs can engage in advocacy to make official data on the SDGs more open and available. Depending on the context, CSOs may wish to urge their government to do one or all of the following:11
• Make a strong public commitment to open data on the SDGs;
• Identify and begin to publish some public information on the SDGs as open data;
• Develop a government-wide policy on open data, through an inclusive process, that sets standards for how the government will manage and release information on the SDGs;
• Create public listings of all government data related to the SDGs;
• Establish new legal rights for the public to access government data on the SDGs;
• Proactively engage with and support data users to access data on the SDGs; and
• Require that open data commitments apply to all organizations handling public data.
2. Promote and support basic data literacy – Data in themselves may not be meaningful without skilled data users who can understand and translate complex information into simple messages for a broader set of accountability actors. CSOs can promote and support basic data literacy for information intermediaries (‘infomediaries’) such as the media, social media users, civil society groups and citizens, as a way to support the use of data as an accountability tool.12 Data literacy skills include digging, collecting, cleaning, analysing, visualizing and communicating data to the public and decision-makers.13
3. Produce and support citizen-generated data – CSOs can play an important role in producing data on the SDGs as well as supporting the production of citizen-generated data. CSOs can invest financial support
and other resources to build the capacity of civil society and citizens – including women, men and children – to collect, process and analyse data on the SDGs, including disaggregated data.14 The production of survey-based perception and experiential data – which measure the direct needs, priorities, perceptions and experiences of citizens themselves – can be particularly valuable in supporting a people-centred approach to accountability for the SDGs.15
In producing citizen-generated data, CSOs should seek to work in a participatory manner with vulnerable and marginalized groups who are often excluded from official data collection processes. Data generated by people in the margins are important to build a deeper understanding of the underlying issues that perpetuate poverty and inequality and to be able to hold governments accountable for their commitment to reach those furthest behind.16 The participation of marginalized groups in data collection and analysis can support their empowerment and help to open up and build a constructive dialogue with decision-makers to promote greater accountability. Further, engaging marginalized groups in producing data on the SDGs may help to address potential concerns about privacy and identification.
CSOs engaged in producing data on the SDGs should take the following into consideration:17
a. Data-gathering methodology – Is the methodology clear and consistent, and does it conform with the basic principles of a human rights-based approach to data?
b. Types of measurement – What are the types of measurement used and how can they be aligned with SDG data-gathering efforts?
c. Verification of data – Can the data be adequately verified in accordance with key principles of data validation and verification?
d. Digital divide – Is there a risk of creating a ‘digital divide’ if the data are generated through internet-based or Information and Communication Technology (ICT) applications?
e. Capacity-building – Are there measures in place to ensure adequate data and methodological literacy of those collecting the data?
4. Engage in partnerships on data – CSOs can seek to establish effective partnerships in relation to data collection, both with National Statistical Offices (NSOs) as well as other key actors such as National Human Rights Institutions (NHRIs), academia and the private sector. There is a significant amount of SDG-relevant data produced by non-state actors that can be brought to the attention of NSOs who may be able to play a role in coordinating data from different sources. Further, NSOs may be able to provide resources and tools that assist non-State data collectors – such as CSOs – to collect quality data and to improve the comparability and usefulness of that data.18 Other actors such as NHRIs may be able to assist CSOs in vetting potentially sensitive data,19 while CSOs can help NHRIs by working with vulnerable and marginalized groups to produce citizen-generated data. Collaborative efforts through effective data partnerships can strengthen and expand data collection and disaggregation for the SDGs and help to ensure that data is shared and easily accessible to all, thereby strengthening the potential use of data for accountability for the 2030 Agenda.
• The Open Government Guide (2015), by the Open Government Partnership, includes a chapter on ‘Open Government Data’ that provides useful information on the steps that governments can take to make data more open.
• The DataShift initiative provides links to online resources that support citizen-generated data.
• A Human Rights-Based Approach to Data: Leaving No One Behind in the 2030 Agenda for Sustainable Development (2018), by the UN Office of the High Commissioner for Human Rights, provides general guidance on a human rights-based approach to data (HRBAD), with a focus on data collection and data disaggregation.
• The Commonwealth Youth Development Index: National and Regional Toolkit (2016) by the Commonwealth Secretariat, provides information on building a local, national or regional level Youth Development Index (YDI).
• Expanding the Data Ecosystem: The role of “Non-Official” Data for SDG Monitoring and Review, by the TAP Network.
• SDG Goal 16 Data Indicators, by the TAP Network.
• Global SDG Indicators: Building a Framework that is Fit For Purpose, by the TAP Network.
• Making them Count: Using indicators and data to strengthen accountability for the SDGs, by the TAP Network.
• The DataShift initiative by CIVICUS and partners aims to build the capacity and confidence of CSOs to produce and use citizen-generated data to monitor sustainable development progress, demand accountability and campaign for transformative change.