New Big Data and Development Fellowship: Apply to work with our Data Scientist

I am happy to report that the Big Data and Human Development Incubator has just recruited a data scientist to work with the network for the next 9 months.

Fabian Braesemann has a PhD in Social and Economic Sciences from the University of Vienna, and has been working as a Data Scientist over the last year. He has experience/skills in diverse aspects of data science and data mining. However, his main expertise is on datafication and the application of data science to social science questions. He will be using the computing facilities at the Oxford Internet Institute.

In order to kick-start some pilot projects within our network, we are proposing that teams from around the university can bid to work with Fabian on small projects that use computational/big data approaches and speak to key questions in human development (we can take a broad view of what constitutes human development, and will consider research that focuses on poverty, inequality, economic development, political voice and representation, activism, and other topics).

We ask that any interested teams submit a 1-2 page pitch. Each pitch should outline what questions the group seeks to answer, what data they seek to use, and what further work this might result in. It should also outline the cross-disciplinary or cross-departmental nature of the work (these bids can be a way of building links or deepening existing links, but should not just be used by teams or scholars within a single department). Please also include short bios of the proposed team members. More details about what we need are included in the bullet point list below.

Proposals could be speculative in nature (scraping data, trialing analysis), but do not have to be.

We hope to ask Fabian to work with three successful teams over his 9 month contract at Oxford, so please pitch an idea that will take roughly 2-4 months of his time either as full time engagement or on a part-time basis. We ask for all pitches to be submitted by March 1.

Please feel free to circulate this CFP. Submit your pitches to Mark Graham, and please get in touch if you have any questions.


  • Projects can address questions in any area of human development.
  • Projects should be completed by March 2018 at the latest.
  • There is no further funding available from the Big Data and Human Development Incubator. In other words, these your proposal will be to work with Fabian, and will not be a bid for any additional funding from us.
  • Projects can be exploratory or at early stages of development. Most important is that you have a vision for how this might turn into a larger funded project after completion of your pilot work.
  • You may work with collaborators outside of Oxford, but the core team should be based at the university.
  • Anyone at the university who is eligible to apply for external funding will be eligible to lead one of these bids.
  • If we receive more than three three month bids, we will distribute all applications to lead-researchers on each of the bids and other scholars in the big data and development network in order to ask them to rank submissions.

Symposium on Big Data and Human Development | Sept 15-16 2016 | Final Programme

This workshop aims to move forward the debate about the ways in which big data is used, can be used, and should be used in development.

This symposium will also serve as a bridge between methodological knowledge about big data, critical academic research on the topic, and the desires of stakeholders and practitioners to achieve key developmental outcomes and goals.

This conference will use the hashtag #datahumdev

With keynotes by:

  • Professor Bitange Ndemo, Former Permanent Secretary of Kenya’s Ministry of Information and Communication, and Lecturer at the University of Nairobi
  • Professor Alex (Sandy) Pentland, Academic Director of Data-Pop Alliance, and Director of the MIT Human Dynamics Lab
  • Dr Linnet Taylor, Assistant Professor in Data Ethics, Law & Policy, Tilburg Institute for Law, Technology and Society (TILT)



Thursday 15 September
Start End Schedule
12:30 13:00 Registration
13:00 13:15 Welcome & Opening Remarks

13:15 14:15 Keynote

  • Dr. Bitange Ndemo, Former Permanent Secretary of Kenya’s Ministry of Information and Communication and University of Nairobi Business School
14:15 14:45 Coffee Break
14:45 15:15
15:15 15:45
15:45 17:45 ‘Health and Big Data’

  • Speakers TBC
Friday 16 September
Start End Schedule
09:00 10:00 Keynote

10:00 10:30 Coffee Break
10:30 11:30 Parallel Session A (Lecture Theatre 04)Title TBC

“The Diffusion of Ultrasound Technology and Missing Women: An Analysis based on Google Searches for India”

 10:30 11:30 Parallel Session B (Seminar Room)“Exploring the Potential of Open Data and Aid Transparency for Development”

“Building the Online Labour Index”

“Emergency Event Detection Using Mobile Phone Data”

11:30 12:30 Parallel Session A (Lecture Theatre 04)“The Economic Geography of the Internet 2.0: Digital Social Capital and Cities.”

“Data, Visualisation and Human Development”

“Measuring the Hidden Contours of the Global Knowledge Economy with Big Data”

 11:30 12:30 Parallel Session B (Seminar Room)“The Making of Beneficiaries: On the Datification of Anti-Poverty Programmes”

“Big data for development research in the Global South: Experiential lessons from LIRNEasia”

“Combining Big and Traditional Data Sources to Enhance Public Policy Decision Making for Sustainable Development”

  • Dr. Jonggun Lee, Pulse Lab Jakarta – United Nations Global Pulse
12:30 13:30 Lunch (provided)
13:30 14:30 Keynote

14:30 15:30 Parallel Session A ( Lecture Theatre 04)“Algovernance: Can Open Algorithms Revive Democratic Principles and Processes?”

“Digging into big data and development: Findings from three Indian cases”

14:30 15:30 Parallel Session B (Seminar Room)“Using IATI Data in “big data for human development” Research”

“Big Data and Development: the Role of Competition Law and Policy”

Title TBC

15:30 15:50 Coffee Break
15:50 16:50 Panel & Keynote

16:50 17:00 Closing Remarks

Symposium on Big Data and Human Development

We are happy to announce a two-day symposium (Sept 15-16) that we are running in Oxford on the topic of big data and human development. This workshop aims to move forward the debate about the ways in which big data is used, can be used, and should be used in development.

This symposium will also serve as a bridge between methodological knowledge about big data, critical academic research on the topic, and the desires of stakeholders and practitioners to achieve key developmental outcomes and goals.

We are lucky to have keynotes lined up from the following speakers:

  • Professor Bitange Ndemo, Former Permanent Secretary of Kenya’s Ministry of Information and Communication, and Lecturer at the University of Nairobi
  • Professor Alex (Sandy) Pentland, Academic Director of Data-Pop Alliance, and Director of the MIT Human Dynamics Lab
  • Dr Linnet Taylor, Fellow at the Department of International Development, University of Amsterdam

Call for abstracts

We welcome the submission of abstracts (of max 250 words) for talks, panels, and sessions at the workshop. Submit them to by 15 July 2016.

Papers presented in the conference will be considered for an edited volume in big data and human development.

Please contact Mark Graham ( with any questions.

The Oxford Human Development and Big Data Incubator is working to stimulate policy-oriented research. Topics that we seek to focus on in our workshop include (but are not limited to):

  • What ‘big data’ can tell us about human development; how we can facilitate better decision-making and accountability in previously data-sparse environments;
  • What presences and absences of data tell us about issues of participation and exclusion among marginalised populations;
  • What tools have emerged globally that can maximise citizen ownership of big data, by making data meaningful within the cultures of participation that characterise different localities.
  • Research results of projects employing big data in the contexts of development.

Submissions may include:

Talks: Contributors are invited to submit full-length talks (15 min) related to the conference themes

Panels: Contributors are invited to pitch a panel discussion on core conferences themes

Demonstrations: Contributors are invited to submit an idea for a demonstration (which may be facilitated as part of a panel as a stand-alone event)

To attend, please email your name and affiliation to Attending this conference is free of charge. Please note space is limited and registration preference will be given to contributors of selected abstracts. Otherwise, check out our official events page for up-to-date information, and hope to see you in Oxford!

Jobs in Big Data and Development

The Alan Turing Institute is now hiring 3-year fellows in social data science and the digital humanities. One of the specific areas that they are looking for is someone who does research at the intersections of big data and development studies.

Check out specifics on their website (closing date July 13).

Using Alternative Data Sources to Validate International Surveys?

The narrative of misleading development statistics has been iterated in recent years. Morton Jerven’s well-known text, How We are Misled by African Development Statistics and What to Do about It, challenges the reliability of development statistics and calls for new approaches to data collection. More recently, Michael Robbins and Noble Kuriakose have determined that approximately 1 in 5 international surveys contain fabricated data.

By reviewing responses from more than 1000 surveys, Robbins and Kuriakose identified 17% of these surveys as “likely to contain a significant portion of fabricated data. For surveys conducted in wealthy westernized nations, that figure drops to 5%, whereas for those done in the developing world it shoots up to 26%.”

The two researchers came to these conclusions by identifying duplicate responses in surveys. One existing hypothesis is that many survey responses are biased due to the presence of data collection assistants (who are often collecting data door to door). Although some researchers have challenged Robbins and Kuriakose’s methods, many others believe that the problem is even larger than the stated 17 percent.

Clearly, there is a strong argument to be had that additional data sources should be used to validate survey responses. One of our objectives at the Big Data and Development Incubator is to understand how data has been effectively harnessed in the context of development. By furthering the conversation on data and development, we aim to support development professionals, practitioners, and scholars.

Big Data and Development: Speed Dating!

Participants outlined some of their “aspirations” for big data and human development on post-it notes.

Participants outlined some of their “aspirations” for big data and human development on post-it notes.

On Thursday, February 4th, approximately 20 Oxford academics met to discuss the Big Data and Development Incubator.  In an effort to understand the potential uses of ‘big data’ in the contexts of development, participants asked what techniques, data sources, and possibilities exist for harnessing new online data to address persistent concerns regarding human development, inequality, exclusion, and participation.

By bringing together researchers with expertise in ‘big data’ and/or development, we hope to encourage the future development of collaborative research projects. From this research, several key themes emerged:


  •   Firstly, many participants raised the topic of data generation processes. Implicit in this topic is both the need for a more narrow understanding of the term “big data” as well as the necessity of a broader conversation focused on the implications of big data analysis


  •   Secondly, another area of interest was the application to “big data” (social media data, GIS data, etc.) to areas currently understood predominantly with “conventional data” (i.e., micro data, household surveys, etc.). Participants asked how information from social media can inform local policy as well as how this data could be linked with existing sources.


  •   Lastly, the possibility of engaging more directly with data scientists affiliated with Oxford globally, and more specifically in Kenya, arose an area for further exploration.

In the coming weeks and months, we intend to consider next steps in each of these areas and plan future forums for discussion. Please reach out to Mark Graham at if you are interested in contributing!

What role for the Big Data and Human Development research network? Reflections from the UN Expert Group Meeting on Big Data and the 2030 Agenda for Sustainable Development, 14-15 December, Bangkok

UN EGM on Big Data and the 2030 Sustainable Development Agenda

Participants at the UN Expert Group Meeting on “Big Data and the 2030 Agenda for Sustainable Development”

(Photo credit: Eri Nomikou,


With a critical view on “Big Data” and “human development” across low-, middle-, and high-income countries, we position ourselves as a unique research network in the expanding Big Data and development landscape. Having returned from a recent United Nations Expert Group Meeting on “Big Data and the 2030 Agenda for Sustainable Development,” I believe that a key contribution of our network is to foster a North-South dialogue and to offer multidisciplinary perspectives and competencies that are largely under-represented among the existing Big Data actors.

Make no mistake: The debate at this high-level forum was nuanced and critical rather than focused on utopian ideas about the limitless potential of big data. Actors from the public, private, and academic sectors agreed that we first need to focus on the development problems and then solve the respective data needs, not the other way round. Problems of data solution “patchwork,” data privacy and consent, viable private sector business models for public-private partnerships in big data, or closed versus open data environments were debated openly and honestly.

But it is also clear that many issues surrounding big data remain unresolved and require critical reflection and research. For example, because the skills and capacity to produce, handle, and analyse Big Data are likely to rest outside of government boundaries, increasing the use of Big Data in policy can be problematic. While often framed under broadening participation (e.g. Twitter data), “partnerships” for a wider data ecosystem, and private sector “data philanthropy” (i.e. companies donating data), private partners might also have vested interests to shape and select the data and indicators that correspond to desired policy changes from their perspective. This could mean a transfer of knowledge and power from the public to the private sector. How could we then ensure that transparency and accountability mechanisms apply to the same extent to private actors as to public ones? Even where such situations do not occur, continuity and reliability in such partnerships are not guaranteed. For example, voluntary donation of data by a company may be useful, but once economic constraints tighten, how would that company be prevented from stopping this practice in order to keep costs in check? How would private data sharing agreements alter if the company is bought by a competitor? What if national development policies are based on data provided by a company that is about to go bankrupt (the same applies to NGOs with erratic income streams)?

My point here is not that Big Data uses for development policy should be discouraged, but that we need to have a better grasp of such fundamental questions before we advocate alterations of fundamental policy processes in favour of non-conventional data (even existing “conventional” data appears widely underutilised). Among the numerous problem areas surfacing at the Expert Group Meeting was the need for overarching frameworks (e.g. ethical, evaluation, data governance, and knowledge management frameworks) and for a better problem-specific and micro-level understanding of Big Data’s opportunities and intrinsic limitations (e.g. the social context of data generation, informational value of Big Data vs. conventional data to monitor specific Sustainable Development Goal indicators). The illustration below summarises some of the many themes that arose in the meeting.



Summary of Big Data problem areas

In my view, the high-level conversations at the Expert Group Meeting serve a useful purpose for putting “Big Data” on the policy agenda. What is needed next (and we are not quite there yet) is to build a knowledge base to understand how and how not to use various kinds of data in development policy and processes. Countries may articulate data and knowledge demands for specific development problems, and work with other “stakeholders” in pilot projects to develop institutional frameworks and mechanisms to make the best use of Big Data in light of its limitations. One plausible scenario might be that Big Data solutions help governments to save money when monitoring variations in development indicators for a majority group in urban areas (e.g. mobile phone data on economic performance and incomes), but the costs saved for data collection in one area should then be reinvested in order to understand the problems of the groups omitted by these data sources (e.g. remote and disconnected population groups). (Pilot projects, despite their seemingly poor reputation at the meeting, can help to build such knowledge, provided that evaluation frameworks are developed to articulate the learning outcomes up-front.)

The participation in a debate among experts has reinforced my conviction that research networks like ours are an indispensable ingredient to a more comprehensive understanding of Big Data. It is especially the North-South dialogue and the interdisciplinary expertise in our network that can open new perspectives and add much-needed depth to a Big Data debate that is still taking place at a high level.

Big data and development mailing list

We have started a mailing list for anyone wanting to stay in touch about the ‘big data and development’ initiative, and engage in conversation with the network. Just send a message to [] to sign up.

The new Big Data and Human Development research network

Data are now almost ubiquitous. Sensors and software are digitising and storing all manner of social, economic, political and environmental patterns and processes. As the size of these datasets has increased exponentially, many have begun to focus on how ‘big data’ harvested from online sources can allow potentially unprecedented insights into our world that may facilitate efforts to enhance human development.

Yet relatively little is known about how best to harness ‘big data’ in ways that could effectively inform development processes, particularly for the most disadvantaged, and whether those at the margins who produce the least amount of data risk becoming even more invisible. While new expertise is emerging, it remains unclear whether, and how, ordinary citizens will be able to seize these opportunities, individually and collectively and use them to their advantage.

Our initiative:

The ‘big data and human development’ research network aims to investigate the potential uses of ‘big data’ for advancing human development and addressing equity gaps. We are establishing a cross-disciplinary and global network to map what data sources and techniques exist for harnessing new digital data and address persistent concerns regarding human development, inequity, exclusion, and participation.

Our Goals:

The goals of this network will be to stimulate policy-oriented research that seeks to understand: (1) what presences and absences of data tell us about issues of participation and exclusion; (2) what data tell us about gaps in human development: facilitating better decision-making and accountability in previously data-sparse environments; (3) what tools have emerged globally that can maximise citizen ownership of big data, by making data meaningful within the cultures of participation that characterise different localities.

Our Approach:

We plan to achieve these goals with three core activities.

1) First, we plan build a digital observatory that seeks to assess the potentials of different data sources for informing human development. This observatory will be a web-platform that can link to relevant data and metadata.

2) Through the use of detailed case studies, we aim to empirically illustrate some of the promises and perils of using big data to inform human development. These case studies will be carried out in collaboration with end-users is some of the countries that most need to access big data and harness them for human development, but lack the expertise to make use of them as they are currently offered.

3) Third, we plan to bring together research and policy from both Global North and South to ensure that methodological knowledge about big data is appropriately mapped on to the interests of stakeholders to achieve key development outcomes. We hope to bring together key figures in order to avoid what Schroeder 2014 refers to as the tail of big data wagging the dog.

Our Planned Activities:

  • An initial workshop will be held in Oxford in the first year of the initative bringing together a limited number of key stakeholders to discern the potential use of big data for human development. This workshop will help inform development of the data observatory and selection of case studies.
  • A core activity for our project is the development and maintenance of a data observatory of big data and its potential for informing human development
  • A final workshop will be held in the second year to disseminate our preliminary findings to a broader range of stakeholders and further engage with the types of empirical research being pursued.
  • We also plan to host a seminar series focusing on ‘big data and human development.’ This will be an open event for anyone in Oxford, and will be freely webcast for a broader audience.

Our hope is that this project will bring together a range of disciplinary strengths at Oxford and beyond. At this early stage, we welcome inputs, suggestions, and collaborations, to steer and guide this initiative. Bringing together work in this area will not only result in ground-breaking, cross-disciplinary research, but will also ultimately serve to inform more evidence based human development programmes around the world.