Late last year, the United Nations introduced
several initiatives to strengthen countries’ use of big data for sustainable
development, including a data literacy platform, a proposal for a 12-point plan
on privacy and governance issues and a mapping software for monitoring progress
on the Sustainable Development Goals.
In January 2016, the 17
Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable
Development, adopted by world leaders in September 2015, officially came into
force. Over the next fifteen years,
with these new Goals that universally apply to all, countries are expected to mobilise
efforts to end all forms of poverty, fight inequalities and tackle climate
change, while ensuring that no one is left behind.
Partnership with Data-Pop
Alliance to promote data literacy
The UN System Staff College (UNSSC),
the primary provider of inter-agency training and learning for staff of the
United Nations system, together with the Data-Pop Alliance,
launched a platform offering online courses on big data in November 2017, and
will conduct face-to-face trainings in 2018.
The Data-Pop Alliance is a global coalition created by the Harvard Humanitarian Initiative, MIT Media Lab, and the Overseas
Development Institute (ODI) to promote the
use of big data for sustainable development through research, capacity building,
and community engagement.
Through the new learning platform, called the ‘Big Data & Sustainable
Development Open Learning Hub,’ UNSSC and the Data-Pop Alliance are seeking
to promote data literacy within the UN and other development practitioners. A
series of eight consecutive modules are being offered over a period of 11
months. The online modules became available in November 2017 and will run until
mid-September 2018.
The first module covered issues of governance, transparency
and politics related to the use of big data, and subsequent modules will
address: climate change; citizen-generated and mobile phone data; gender
equity; public health; emergency response; data collection, gaps and
opportunities; and data storytelling and visualization. The programme can be
accessed by anyone who creates a profile on the learning hub.
UNSSC and the Data-Pop Alliance are also offering in-person
training on ‘Leveraging Big Data for Sustainable Development.’ The training will
be conducted over three to four days, and is offered in French and English at
various locations around the world.
A French-language programme is scheduled to take place in
Dakar, Senegal, from 6-8 March 2018, and an English-language programme in
Bangkok, Thailand, from 27-29 March 2018. The training programme is meant to
strengthen the skills of UN staff and development practitioners in selecting,
creating, using and interpreting data in support of the Sustainable Development
Agenda. The Hewlett Foundation is
supporting fellowships to cover the costs of the course to professionals from
public sector institutions, civil society and academia.
Proposed 12-point roadmap
for addressing privacy issues
Emmanuel Letouzé and David Sangokoya of the Data-Pop
Alliance have proposed a 12-point roadmap addressing privacy issues in big
data. In a paper titled, ‘How
to Use Big Data,’ (roadmap available on page 19 of report) developed in
cooperation with the Vodafone
Institute for Society and Communications, the authors recommend Putting
‘privacy by design’ into action. The paper suggests four categories of privacy
engineering solutions and design strategies for big data use:
Distributed Data Repositories (Model in which different
kinds of data are stored in separate repositories and tools are deployed from
an external or remote human query that can send queries to the correct data
repository
Move the Algorithm to the Data (Distributed, Privacy-Maximising
Algorithms): Model in which each data repository enables remote queries to send
their query statements or algorithms to the repository.
Data Always in Encrypted State (at Rest and in Computation):
Model in which data is always in an encrypted state and new cryptographic
algorithms and approaches allow operations to be carried out without need to
decrypt first
Encode Data Usage Agreements in Legal Trust Networks: Trust
network model for large scale data sharing in an ecosystem, combining computer
network tracking user permissions for each piece of data within a specific
legal framework.
The authors recommend that all stakeholders—including companies,
privacy experts, policymakers, data scientists, data users, private sector and
ethicists—should co-create infrastructure and spaces for discussion, safe
experimentation and transparent findings.
They go on to say that new data public private partnerships must
make transparent for all data stakeholders where and how the data is shared and
what kinds of public problems will be solved through these data innovations in
order to build public trust.
Geospatial measurement
of progress on SDGs
The UN Statistics Division with the GIS software company
Esri have set
up a data hub enabling countries to use mapping software to measure,
monitor, and report progress on the SDGs. This new hub, called the Federated
System for the SDGs, is based on Esri's ArcGIS platform and will use location
intelligence to make it easier for countries to collect, analyse, and share the
data required to monitor progress.
This was first introduced as a research project and six countries
participated in this invitation-only phase, Ireland, Mexico, the Philippines,
Qatar, South Africa, and Senegal. These countries helped define the
requirements and deployment of a web mapping and data management platform that
would eventually become the hub.
Federated system of
open SDG Data Hubs
On 30 November 2017, the Fifth High Level Forum on UN Global
Geospatial Information Management endorsed the concept of a “federated
system” of open SDG Data Hubs.
A Federated Information
System for the SDGs
Overview and Discussion
The federated system aims to enhance the role of national
statistical offices (NSOs) in managing statistical and geospatial data through
an open data platform with software for GIS (geospatial information system) and
data analytics, as well as through the use of web-based tools for communication
and user engagement.
The system also seeks to improve data interoperability from
a wide range of sources through the National SDG Data Hubs and enable the
overlaying of multiple national and global data sets, to understand data flows,
and address inconsistencies.
The concept has been implemented through initial
research conducted by the UN Statistics Division (UNStats) and Esri, which came
together to set up the previously mentioned data hub.
