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Towards a data users’ framework to advance Sustainable Development Goal 2

The framework draws from the working group’s key assumption that achieving accountability for
SDG2 is not possible without scaling up efforts in investments throughout the full data cycle, in-
cluding from standard setting to designing evidence based policies. While the assessment part seems
intuitively the most critical element of the data centred framework, other aspects are also dependent
on the availability of quality data. Both communication and enforcement mechanisms can operate
effectively only if there is reliable evidence supported by data at the different levels. Communicating
about local and national budget allocations for nutrition specific and nutrition sensitive interven-
tions can only happen if supported by validated results. Improvements to policies and practices per-
taining to nutrition and food security and sustainable agriculture require regular monitoring and eva-
luating, and best practices can be developed and applied if relevant empirical evidence is available.
Global nutrition related indices, such as the Access to Nutrition Index and Hunger and Nutrition
Commitment Index, tend to be regularly re-evaluated and re-calculated, and methodological im-
provements can be made based on new data, tools, and methodological advances.

4 Towards Evidence-based Accountability: A Charter of Principles

We find that the following principles are most relevant from the data users’ perspective: standardisa-
tion/alignment, transparency, innovation, institutional framework, and the overarching principle of
sustainability. Summary of suggested policy solutions for data users is provided in Table 2. In terms
of standardisation/alignment, the key questions are around best legal and regulatory practice and
licensing agreements which should be put in place for data collectors, data users, and data standard
setters to adhere to. Here, it is critical to develop a detailed set of standard food security and nutrition
(FSN) related indicators and innovative measurement tools. Creation of the UN Inter-Agency and
Expert Group on Food Security, Agricultural and Rural Statistics to document best practices
and create guidelines, concepts, and methods constitutes a positive example of tackling challenges
related to gaps in standardisation. Another relevant example is FAO’s work on developing new
guidelines for the 2020 World Programme for the Census of Agriculture for the Period of 2016–2025
(UNSC, 2015). From an IT perspective, a unified application program interface (API), such as one-
data.org, could act as a mediator and façade between the users of the API (decision makers, civil
society organisations and researchers) and changes to the core source systems (various AgFSN re-
ports and datasets provided by sectoral experts, NGOs) that provide the data. This would shield users
of an API from changes to those source systems as an API could implement logic to maintain the
structures and methods that applications have been developed against. For example, JavaScript Ob-
ject Notation (JSON) is a schema-less standard which is particularly suited to allowing new data
to be incorporated without impacting previously developed solutions.
Second, transparency involves open data formats used by all organisations providing data. The
reports and datasets must be available in open data formats in real-time, or at least as close to
real-time as possible, to allow for the latest data to be extracted from all reports. PDF reports and
other closed datasets limit the use of data, and the common tried and tested formats for such data are
in XML and JSON formats. JSON is quickly becoming the de facto data format for web and mobile
applications, due to its ease of integration into both browser- and server technologies that support
JavaScript. JSON also allows for an easier integration with web-based mapping technologies such as
Google Maps and Open Street Map, which is particularly important, giving the data users’ aim to
geolocate the information within the accountability framework. The data that are made available and
used within the accountability framework must be designed with customer-facing (local community,
decision maker) applications in mind and the data’s output is designed to be easily understandable,
and supportive of common customer-facing application use cases.
Implementing effective solutions would not be possible without innovative approaches and tech-
nologies. Hence, the third suggested principle is around innovation, in particular the innovative use

72 International Journal of Population Studies | 2016, Volume 2, Issue 1