UN Data Revolution - Part 3

This will be my final post on the UN report 'A World That Counts' which seeks to locate the UN's role in the wake of the data revolution. In previous posts I have outlined some concerns with the report, it's articulation of notions about citizen engagement, ideas about development and also the role for private companies in this picture. 

Several interconnected but useful commentaries have surfaced in recent months which I have read with interest in regards to the report. So looking back at the report here are some which I think I would mention. 

Morten Jerven - The problem with the data revolution in four Venn diagrams

Morten Jerven writes in this article for the Guardian that we also should be critical of the limited view presented by the report in terms of it being a roadmap for action. Jerven presents a series of venn diagrams to explain why. He makes four key points in regards to the report:

1. Not everything that counts can be counted
2. Data is not the same as statistics
3. More data does not mean better decisions
4. There are other methods to knowing than through counting

He asks us to consider how much we should invest in numbers and what type of metrics we should invest in?
He warns against against hubris. As he puts it, the act of counting itself does not guarantee objectivity or always make us wiser.

Michael Hobbes - Stop Trying to Save the World

 

A second and wider critique of the entire development agenda comes from Michael Hobbes at the New Republic in this article. He suggests we should clearer about what doesn’t work or has shown less success so far, this is a new area with an open field of possibilities. There is no need to replicate poor ideas. 

His article makes for very engaging reading and the implications are too deep to try to expand in this blog post. He points out that he prefers to suggest that it is not that development is broken, but the problem is that our expectations of it are.

The critique of the report might be that it sketches out a landscape, but does not go far enough to move away from the status quo. It attempt to fire up the imagination, by seizing enough of what matters to bring forward discussions about ‘for who’ and ‘for what’. But it does not look critically enough at what needs to change in the established regimes of how international development is conceived of in its ideas about how to harness the data revolution.  

Another associated point to consider is how the report attempts to bend towards a rights based view of how data governs our lives. There is a tendency for those within ICT4D to seek technical solutions rather than to follow the doxa, and often these efforts tend not to be based in rights based language. This seems most often to express a desire to bypass voice, to find a way around the existing channels of arbitration and consensus in the public space – think niche, think geek. This is a difficulty for the report in that is seeks to adopt the language of human rights, but it does this in a limited way as it has to stretch the terms used around some very broad and fuzzy concepts.

The point that Martin raises is that for aid to work as assistance for functioning democracies, governments and civil societies, it needs to be self-limiting – consciously eschewing big ideas and paying constant heed to local conditions. He also takes his cue from many of the debates around behavioural economics that have been pushed forward by the research of the J-Poverty Lab and others and have sought to challenge a lot of conventional thinking about development.  

 

Jed Miller's blog post - Will the Data Revolution Be Well-Advised?

Jed gives a more or less balanced appraisal of the report in his blog post saying that it is strongest where it seeks to ensure inclusion in the data revolution. From his persepctive the two oversights are its underestimation of the role of civil society and its over-reliance on the notion that citizens equipped with accurate, usable data can be successful independent agents of social change. He points out that it suggests:

"an idealized, if not unexamined, vision of a super-citizen with the ability to leap over entrenched political, economic and bureaucratic barriers using crowdsourced data, or hashtag campaigns or data APIs"

Tiago Peixoto  - Evidence of Social Accountability Initiatives

 

Tiago Peixoto in his blog post highlights an interesting paper on evidece around social accountability inititatives which chimes quite well with the above mentioned posts. The paper by Jonathan Fox suggests a necessary distinction between tactical and strategic approaches to the promotion of citizen voice to contribute to improved public sector performance.

Fox suggests that tactical interventions tend rely on optimistic assumptions about the power of information alone both to motivate collective action and to influence public sector performance.

In contrast, strategic interventions are multi-pronged and encourage enabling environments for collective action and also bolster state capacity to actually respond to citizen voice. Not simply focusing on the supply of information or data, but also on the demand and the capacity to act effectively around this.

There is also a neat diagram to demonstrate what this 'Sandwich Strategy' looks like:

Tim Davies - Unpacking open data: power, politics and the influence of infrastructures

 

Tim Davies gives a concise and beautifully illustrated talk (thanks to the amazing Willow Brough) addressing some of the questions around the "anticipated civic impacts" of open data. He looks at how changing regimes around data can reconfigure power and politics, and the limits of current practice. He then attempts to re-imagine the open data project, "not merely as one of placing datasets online, but as one that can positively reshape the knowledge infrastructures of civic life". 

Matt Stempek - Why Use Private Data For Public Good

 

Matt Stempek wrote an article for the Harvard Business Reveiw in July of 2014 titled "Sharing Data Is a Form of Corporate Philanthropy". In it he focuses on just two key areas that are proving to be game-changers for data - responsive cities and academic research. 

In regards to my critique of the UN Global Pulse's adoption of the WEF's vision of data as a 'resource' for economic progress the UN Global Pulse in fact also did hold a meeting in 2014 to discuss this very issue which is detailed here. The same topic is picked up by Tim Davies in his blog post here.

In the light of of these critiques I think a key question that surfaces is that of citizen engagement in this process. Either we find ourselves overselling or underselling citizen engagement as a factor in these discussions. In the spirit of this discussion I would put forward a few questions that spring to mind, or at least a few myths that present themselves as in need of busting one way of the other. These might be summarised like this:

Some Myths About Citizen Engagement

 

1. Engagement is too expensive

2. Citizens aren’t up to it

3. Engagement only works for easy issues

4. Citizen Power is a floodgate we should avoid at all times

5. Citizens don’t want to be involved they just want good services

Like all good myths they are not true in the strict sense of the word. But there is also a grain of truth in each of them which explains their durability for policy makers and government bodies as blind yardsticks. There has also been far too much talk around citizen engagement as some kind of one dimensional derivative of other things. It is like saying that all you need to do to make this particular tune rock is to turn the volume right up. It looks like it might work, but usually doesn’t.

It would be great to see a potential list of 'Myths about Private Sector Engagement' too..Maybe something to think about, or at least to bear in mind for 2015. 

So we need data - for what?

This is a second blog post following the launch of the UN report on the ‘Data Revolution’. I'll be exploring my own ideas, and also trying to outline some ways that complexity theory is being used to work in this space. I'll also see if I can illustrate some points from my previous post as well. I am slowly rolling these ideas along, which appear to have first been scribbled in apparent frustration on a post-it below (there were many more). This is from a collaboration and discussion that took place earlier in 2014 at the Open Development Fringe Event at OKFest in Berlin. 

Brainstorm At Open Development Fringe Event 2014

Creative Commons Licensed (BY) flickr photo by tomsalmon: http://flickr.com/photos/fishytom/15185058154

One of the biggest challenges facing policy makers today is complexity, and this relates in interesting ways to ideas about a ‘Data Revolution’. There are quite a few initiatives working out ways to understanding the limits to governing and acting instrumentally to fulfill policy goals. The OECD published a piece on ‘Applications of Complexity Science for Public Policy’ in 2009 and I'll take that as a fairly good indication of it being on the horizon of mainstream public policy debates. I am not particularly familiar with approaches that are established in terms of dealing with 'complexity'. So my understanding is that complex situations might lead people to offer preventative policy approaches, others might adopt resilience terminology while a final group makes up a more transformative paradigm. I'll try to avoid rolling them all into one, as I am sure that not all approaches are equal or have the same notion of complexity embedded in them. I also have not yet come across any 'approaches' that see a particular virtue in making any claims about 'disruption' either, but I will keep my eyes open...

So take the recently published UNDP Human Development Report 2014, which proposes as its central idea the concept of ‘human vulnerability‘ as a paradigm of complexity for development in the future. It goes on to describe the prospects post-2015, particularly of development and growth eroding people’s capabilities and choices, and argues for a sustained enhancement of individuals’ and societies’ capabilities with a particular focus on collective action to counter this.

It puts forward an argument about ‘structural vulnerability’, which as it is proposed in the report seems to go further than ideas of ‘risk mitigation’ or a more limited ‘resilience type’ approaches to generate a clearer picture of how inequality interacts with interventions and actors. So as the report points out, eliminating extreme poverty is not just about ‘getting to zero’; it is also about staying there. It strongly adopts the language of capabilities for individuals, and cohesiveness and responsiveness for institutions and societies describing both how affirmative action and rights based approaches fit in to this picture as well as openness, transparency and accountability initiatives.

A simple message might be that this is one way of looking at adaptation in complex systems going through processes of change and innovation. Discussions around the 'data revolution' also seem caught up in an emerging tangle of efforts around this, although of course there are different takes on the ideas from different stakeholders.

For example one corner there is some interesting work going on with looking at how to solve complex problems better at the Kennedy Centre BuildingCapacity Program and the ODI where they are talking about ‘Doing Development Differently’ (yes: #DDD) and Problem Driven Iterative Adaption (yes: #PDIA).

At first glance some of the language about ‘politically smart development’ from them appears at some point borrowed from programs like the Developmental Leadership Program (DLP). However, the emphasis is in fact more on thinking about design as a paradigm and using design thinking with problem solving approaches like the 5 Why’s, problems trees and fishbone diagrams (the Ishakawa diagram). The Kennedy Center strongly references Hirschman’s ideas and approaches quoting the “Principle of the Hiding Hand” proposed by him:

      “men engage successfully in problem-solving [when] they take up problems which they think they can    
       solve, find them more difficult than expected, but then, being stuck with them, attack willy-nilly the 
       unsuspected difficulties – and sometimes even succeed.”

I have to say, to me this is not so much a statement of approach, but it certainly sums up a lot of my experience of 'problem solving' within large slow moving organisations that are not particularly good at encouraging divergent thinking. Another way to put it, as Matt Andrews does in his blog is that people have strong incentives to opt for 'big best practice type initiatives' and will also tend to 'overestimate the potential results'. So let's imagine upfront that we accept a degree to which path dependency and institutional constraints affect thinking in our organisation. Then the only real 'problem solving' that is really going on is in the attempts to devise a means, at each step of the process, to reconcile 'unsuspected difficulties' with the received 'best practice' methods. In some ways this seems to relate to a lot of the ideas around Agile Development and Open Development as well, but is probably from a different perspective. It also speaks to Easterly's long-standing distinction between 'planners' and 'searchers' in development, which is also championed by many market-based approaches to development work.

Let’s illustrate this in a context which is broadly the one that this blog post is addressing. The UN report is highlighted in a recent economist article on the ‘Data Revolution’, and states that a key problem is simply that there is an ever growing and expanding divide between the data rich countries and the data poor ones in terms of data. The article helps to paint a picture of why some of the slow moving machinery based on national statistics and silos of project data around the MDG’s is unlikely to be fit for purpose to be responsive to the shifts and shocks (like Ebola) that could impact on the post-2015 world. In fact it takes Ebola as a prime example of why real-time data is so important in an interconnected world.

The Economist goes on to explain that Humanitarian action is being hampered greatly by the lack of appropriate data on the location of hospitals, with poor maps of cities. Volunteer efforts with Humanitarian OpenStreetMap Team and charities like MSF and the Red Cross have led the way in creating MissingMaps.org which is trying to create free maps of cities across the developing world, particularly in potential trouble spots before they need crucial data in a disaster situation. Similarly it mentions how call-data from mobile-phone operators in an interconnected world can be put to use by for example comparing data on malaria outbreaks and on people’s movements to make predictions of spread. This seems all the more pressing considering the current situation of disaster around Ebola.

Interestingly the Economist then goes on to describe a role for the private sector as well. It points out that Premise (a startup in Silicon valley) is being used to spot trends such as the fact that as the number of Ebola cases in any one location rise, the local price of staple foods also increases dramatically. As they point out in recent weeks as the number of cases fell, prices also did. The Economist then goes on to say that the authorities already did realise that travel restrictions and closed borders would have this effect, but now they have a way to measure and track price shifts as they happen. The creators of Premise describe a little bit of what is behind their thinking (and success) here. For some of the analysis in the press around the relationship between Ebola and food prices and some of these concerns, there are articles here and here also.

"World Food Programme in Liberia 002" by 26th MEU(SOC) PAO (U.S. Marines) - 26th Marine Expeditionary Unit (Special Operations Capable) Public Affairs Office. Licensed under Public domain via Wikimedia Commons.

I think this returns my attention to the issue that I have sketched out in my previous post. That in essence the Economist is celebrating the work of ‘Premise’ and others like them because they will allow food distribution companies to continue doing business without interruption globally despite the Ebola crisis and the subsequent closing of borders and quarantines.I am not entirely sure that is exactly what the creators of Premise themselves envision for their platform, which seems to be aiming to be working for the social good in a very innovative way.

The way the Economist presents this is actually not as an initiative focusing on development per se, although it certainly could be good for the companies involved. A potential benefit might be if we are able to use the data from ‘Premise’ and other companies in an open way, reusing it and remixing it in order to help predict disasters and improve coordination of relief efforts for example. But the fact that people can make money out of this as a business is not the most interesting aspect of it. The question here should be how is it that corporations and businesses could play a more useful role in contributing to the ‘data divide’ in the global south instead of just focusing on a bottom line.

My question is also how much institutions like the Economist and the WEF are presenting a fairly narrow view of open development, and open data here and are actually pigeon-holing it into simplistic streams? The volunteers who map out cities and the companies who need only focus on how much extra profit the emergence of data about the developing world will potentially bring them in the long run.

The point is not that Premise (the Google funded startup) is designed to make a profit out of its analysis of financial data. Or as the FT article puts it 'Premise taps into hunger for real-time data'. The point is this is how the Economist and the FT have chosen to present it to us.

So to return the argument I proposed in my last blog post. At first glance the WEF is fairly comfortable with designating our personal data is a new class of asset, (see the report here) and like the Economist it probably sees that there is nothing wrong with this or with anyone else selling off analytic data on financial markets in order to supply the market with real-time data. But beyond this they are both fairly silent about is what responsibility the private sector might have to help to mitigate the impact of a humanitarian crisis like Ebola.

Potentially it seems quite likely to be hard to predict a crisis and to map out an area in the event that a crisis might occur there. One the other hand, to ask companies collecting data from the developing world to consider broadly that their work could play an important role in alerting people and agencies to things like price increases in the context of a global epidemic like Ebola seems like a very useful and effective measure.  

The role of open source software and open systems is also important here, because it is helping to build systems for data collection, and useful corridors and channels for information to flow. It is showing itself to be of key importance in the current fight against a threat like Ebola. This story from AllAfrica highlights some of the ways that NGO’s and others are using open systems. A great resource is a recently published book edited by Matthew L. Smith and Katherine M. A. Reilly from MIT Press which is digging into what ‘Open Development’ is and may seek to achieve in the future. Also to point out is the long standing work that rOg media in Berlin has been doing in South Sudan and work that that Stephen Kovats from rOg has already done with UNESCO too on this here.

If you consider how much is being done with open software, it begs the question. Why are we not also asking companies that have useful data and resources to think more clearly how they can move towards making them open? Is it really ever going to benefit poorer countries in Africa with less data to work with and less digital infrastructure if in the end all we are doing is focusing on selling food price data on regions in crisis to the market instead?

To return to the problem of complexity here, I think this illustrates why we have to think outside of the ‘boxes’ that we might be at first tempted to approach these problems with. Part of my argument is that this drive to work with open data in development should not only try make sense of the obvious challenges and opportunities for development actors in a post-2015 world, but also to make sure that it is taking on board Hirshman’s call for more lateral thinking.

Seeking to predict and plan for disasters that will require local solutions, and provide maps and data to aid NGO’s, local governments and local actors to act effectively is clearly valuable. However, an equally predictable effect of a crisis like Ebola anywhere is that markets will act in unpredictable ways and may even exacerbate the situation, and will capitalize on their access to real-time data and analysis to avoid being affected by it. Given the digital data divide, it seems that a more lateral approach to the situation would also be one whereby complex problem solving is employed to test out ways to yield benefits by matching up those who can deliver solutions best with those that have the knowledge, resources and data to assist in this. Not by working in silos, or neccessarily by competing with large 'best practice' initiatives and not by recreating proprietary systems that lead us further towards broadening an existing digital data chasm between the richer and poorer countries around the world.

So in my next blog post and will try to take a closer look at the report itself.    

Who is 'data' really ?

I have been listening recently to discussions about data, often in the context of transforming something or often with critical implications for some bottom line, at other times with claims about it being by nature 'disruptive'.

But increasingly I am beginning to suspect that many of these intertwined discussions are fundamentally different ones. Or at least, that people mean quite different things and actually have quite different thought processes behind how they wish to present 'data' in any given case.

For example if I am talking with people about Open Data it is quite a lot easier. The crowd who do this are very clear about what this means for them. Here and here are posts from Open Knowledge advocating for these standards.

Data varies in terms of structure, use, and things like relevance and other qualities in different contexts. 

Then there are different types of data: open data, big data, etc...and the boundaries sometimes get blurred.

In terms of big data for example the defnition put forward by SAP from a business perspective points you to the qualities of the data, eg Volume, variety, velocity, validity.

This is a much more technical and ‘neutral’ definition really compared to the definition of 'big data' from UN Global Pulse for example. From the outset the concern is less about users, sources or use cases for the data.

Does it matter which definition we use? Well, I think it does but often in subtle ways. Agencies like UN Global Pulse are fairly clear about focusing on big data for global development. So it is really looking at a use case or context for application. I think it is also worth bearing in mind that the document seems to locate the construction of this definition at some time subsequent to meetings of the World Economic Forum and also of the G20.

To me this raises another associated question sort of by implication. For any agency or policy mission it is almost impossible to escape this - it is part of the whole business of making policy. In fact it is really hard to talk about something without thinking about what it is for. Inevitably the interests of certain groups become represented in the process.

So for UN Global Pulse we are looking at big data within international development or developing countries particularly with the G20 in mind, so with an emphasis on economic activity. Consider also that UN Global Pulse does not have direct involvement with UN agencies such as the UN Department of Economic and Social Affairs, or the United National Economic and Social Council (Ecosoc). So you might potentially expect a different vision again could easily come from other areas within the UN even.

Robert Kirkpatrick, who is the director of UN Global Pulse , gives a pretty clear interview here about what UN Global Pulse is, as he says it is a sort of R&D lab based in New York, Jakarta and Kampala.

There are reasons why it matters, and what the 'user case' is going to be. For example the issue of privacy particularly is one of the most obvious problematic areas with how big data is being presented and discussed in this document for me. If you look at the diagram from the World Economic Forum white paper that UN Pulse uses here, you can see that privacy concerns do surface at two levels but not at all clearly for private industry:

It simply mentions questions about ‘Ownership of sensitive data’.

In terms information streams relevant to global development it highlights these four:
- Data exhaust
- Online information
- Physical sensors
- Citizen reporting

Recently at the Open Development Camp in Amsterdam, I was able to listen to discussions and work going on around this area particular.  I think it is one that has been overlooked, but partly also crowded out by the language that gets adopted, in exactly the way it has been above. In a way it also has been silenced.

Check out the presentation here from the ODC in Amsterdam on "Responsible Development Data" and also download a copy of the great handbook that was written during the booksprint with the Engine Room and check out some of the discussion going on around this at Open Knowledge.

In case you want to see the other great presentations from ODC, they are all available on Vimeo here

So why does matter who creates the frameworks? Well, although the WEF sees a role for the private sector in the diagram above in terms of ‘managing and collecting’ consumer data, the vision in this document seems to mostly skip over how one huge area of data could really be made use of to protect people from shocks and price changes. That is of course the data produced and held by corporations on their own activities and those of consumers. It does mention how we could make inferences about the prices of food from interactions via mobile phones with banks, but it does not say how we could inform consumers or even small businesses about the movements of global corporations, exchange rates or even of their own government in order to manage price shocks for example.

Furthermore the use of terms such as ‘stock levels’ of data, and the constant reference to measuring things such as school attendance is more suggestive to me of seeking to optimise and work around concerns about human capital, productivity and efficiency. In short it tends to situate human activity and society very much within the gaze of a corporate understanding of the world.

The microeconomic / optimisation of bounded rationality type decision-making  / predicitive modelling and closed feedback loop type solutions all appear founded on a concept of living in a world founded upon a paradigm of inevitable risks and shocks. I personally think this is a dangerous and slightly spurious argument. It serves I think to lead us to default to placing nearly no emphasis on deliberative proceedures or processes. I mean if we are talking about work in 'international development' then really it presents quite limited scope for human agency in the conception of big data for development here.

It really seems to be advocating for a sort of social fire alarm and spinkler system powered by streams of automatic data. But it assumes in a way that we are living inside the machine, and like Sunstein and Thaler’s idea of the nudge, it is not really about choice but about modifying choice architectures that sustain an equilibrium around a volatility inherent in the system, both via feeback loops and millions of automatic corrections. All of this for me almost instantly assumes that forms of consent to this are automatic or simply fundamentally broken or degraded to a virtually meaningless degree.

Today another important document was released by the Independent Expert Advisory Group on ‘data revolution and sustainable development'.

NGO's particularly have been critical of the weak representation of CSO's around the UN 'data revolution' discussions, see here and also here.

The press conference just went out here.

You can access the document itself and also details of the consultation and judge for youself if you think that it represents a fair process or not. Here is the report in full.

It looks at two key areas in terms of the 'data revolution' for sustainable development:

• The challenge of invisibility (gaps in what we know from data, and when we find out)
• The challenge of inequality (gaps between those who with and without information, and what they need to know make their own decisions)

I will be continuing to blog about it in my next post. 

Open Development & Open Data - Challenges and Opportunities

Global Development Professionals Network in London ICT4D Meetup:

'Open Data in Development' and 'Open Development' has sort of come of age. Global financial institutions, recipients of aid like Kenya, donors like DFID and the Bill and Melinda Gates Foundation see potential in the arrival of open data to the development world, as posts by Chris Gingerich and Saara Romu indicate

The World Bank has recently announced a formal partnership with the Open Knowledge Foundation and the Open Data Institute in London to work together over the next three years. In addition to this, another World Bank initiative called the Open Development Technology Alliance (ODTA) already has 7 draft reports out on the subject.

Organisations such as Publish What You Fund and Ushahidi have been doing it all since 2008. The Open Knowledge Foundation (2004) also has supported these efforts and many others, acting as the broad umbrella that brings open data people together, coordinating working groups on 'Open Development' as well as one on Open Sustainability with blogs, and resources like this simple video from Open For Change. It describes how opening up different forms of content, using licenses and standards can generate new forms of collaboration to achieve different goals in development work. Open for Change was also behind the Open Development Camp 2013 which recently took place in Amsterdam.

Harnessing open data to be used for development work may bring significant benefits. Overseas aid and humanitarian work could be made effective by using data to challenge many of the assumptions that are often wrongly made about developing countries and disaster situations. Data can be opened up for different groups to use in different ways to help tackle corruption and may even encourage policy making to be based on harder evidence. High expectations for those involved in the delivery of aid to be transparent and accountable are most likely to increase, not diminish. For example, this might have implications for a body such as the Global Fund that is being accused in the British press of having watered down its own reporting and auditing proceedures.

Even broader questions though were posed at this camp in November, to be considered. How can open data, innovative technology and new ways of working help us create a better world? How relevant is open data when you live on less than $1 a day? How can we avoid yet another divide between the haves and the have nots in this shift? What are the security risks?

NGO’s and foundations working in development are also not the only ones getting involved. The UN has also been working on opening up its practices and its data. The UNDP for example has recently launched its new open data platform and work is continuing on other projects such as the Common Humanitarian Exchange Language which is coordinated by the humanitarian agencies.

Recently at a meetup on the 26th of November, a group of 58 people at the Mozilla offices in London met to dig into Open Data for Development. If you missed it and would have liked to have come, there will be more events in the future and the OKFN will hold a big conference in Berlin in July. The event was organised by the London ICT4D meetup group and by Eliza Anyangwe who runs the Guardian Global Development Professionals Network. This is a summary of the discussion, along with some observations. Please do add feedback to this post here in the comments section below, and any comments that you wish to add are very welcome.

Eliza Anyangwe brought along an engaging panel, consisting of Ulrich Atz (Open Data Institute), Heather Leson (OKFNlabs) and Claire Provost (Guardian Global Development) who were asked to address two questions:

- What are the hopes and aspirations for open data / open development

- What are the challenges and obstacles ahead?

                                                                                                Photo by Daniel Fowler

A good contingent of ICT4D researchers also attended along with doctoral researcher Tony Roberts, spiritual sherpa and founder of the ICT4D London meetup group with a squad of researchers from Royal Holloway. The academic community were well represented with Duncan Edwards from IDS (who has written on this topic here), Vanessa Thomas from the HighWire Doctoral Training Centre in Lancaster, Gregory Grisha Asmolov from the LSE and Geraud De Ville from the Open University. It was also great to have representatives from many organisations and NGO’s including Aptivate, One World, the IRC, Africa Gathering, CIFOR, Publish What you Fund, and of course the OKFN.

Eliza Anyangwe has written a recent piece for the Guardian on this topic, and kicked off the proceedings with a provocation looking back at Florence Nightingale’s use of data visualisation techniques in her own campaign for changes in health treatment in the British army. Not only did her complex and innovative graphs present rich data, they were also constructed to prove a point. Her analysis and representation of the causes of death and disease bordered on advertising for her cause. With data visualisation now having become so ubiquitous in journalism and in the media, are we getting to a point where we are simply losing the ability to distinguish between information and misinformation? If open development work proceeds in a similar way, what happens if the data quality is not addressed adequately? What are the things getting lost in the glare of data visualisation?

Heather Leson from the OKFN stressed the importance of having the right kinds of feedback loops both in terms of feelings and methods. Feelings count because they indicate how to build trust in the sources, or whether people understand the data. People often don't trust the data unless they are involved in the data collection. Until we talk more about how we involve citizens, then we won't know how to get the right feedback, the remixing and re-use of data that helps to get a more accurate 'open data picture'.

In terms of methods, she pointed out that standards for interoperability are important, referring to a clean Dataset Guidelines list. She pointed out how important it was in an election project with Ushaidi to have communities involved in cleaning data in real time. Examples were also given of data cleaning projects using machines to do this.

Finally, Heather focused on the need to teach and build data literacy. The School of Data has held experimental training workshops for early adopters already. We now need to think more about the question of how to cross the gap between these initial efforts and reaching the next 1000 datamakers in civil society and government.

Ulrich Atz, the head of statistics at the ODI provided some further concise reflections. He pointed out that it is not just about making data ‘beautiful’ but that ‘openness’ involved addressing specific technological, financial and legal hurdles. He made the point that bad data also stifles innovation, leading to problems for sustainability of the whole enterprise. The lack of standards creates inefficiencies that create barriers to data re-use. He pointed out that we need to think about more than just transparency, and consider the role of data within the whole ecosystem. Before it becomes fit for purpose, it is important to test the quality, reliability and validity of data.

He focused on the power of standards and on the ODI’s work on creating certificates for open data. This is a kind of badge that links to a description of your open data. The description explores things like how often it's updated, what format it's in, who and where it came from. For more information see the ODI’s work on this here.

He also made a call to action for us to collect success stories and to remind people to keep holding governments to account for the pledges that they have made to make their data open. He pointed out that a lot of attention had focused on the potential social value of open data, but relatively little had focused on the environmental or economic benefits and possibilities.

Claire Provost who works for the Guardian on global development issues made several points from the perspective of someone at the sharp end of using open data for journalism in the public domain. Timely data can come at the cost of better quality data, and there is often an easy conflation between data journalism and visualisation. Learning to apply the same journalistic scrutiny to datasets as other sources is crucial, and tools that assist in making the process of evaluation of datasets dynamic (such as the aid transparency tracker) are very useful. This tool gives you the ability to understand the plans from various organisations on publishing data, the data fields across all their plans, and gives an analysis of their commitments to publish aid information. Another potentially useful tool mentioned in discussion was also the P2P search engine Yacy. As Clair put it, for the investigator it helps first to know exactly what you don't know.

From her perspective as a journalist it seemed that high stakes questions about the right to information still often are where to start digging. There are many situations in which a well placed request for information, the process of demanding the right to certain data for a story is often the most effective way of fact checking and getting the story right. At least you'd assume the process itself reveals a lot about who is and who is not being given access to data.

The group discussion that followed touched on many points, with journalists, activists, and data scientists approaching the same questions from different perspectives. But here are some of the major points: .

1. Negatives:

We do need to look at negatives as well as positives, and look at situations where open data is not working well. Rufus Pollock at OKFNlabs has recently posted on the topic of Bad Data here.

2. Ethics:

We need to consider ethics as well and realise that in different fields ‘open data’ practitioners can be led into high stakes conflicts, such as on land title issues. An interesting perspective on ethics, informed participation and informed risk-taking is also been posted on the OKFNlabs blog here.

3. Experiment:

We should encourage people to try and experiment and see what happens. Mark Brough pointed to work he had just done on tracking aid to the Philippines here and to the potential for quick, agile and effective action by data wranglers of all kinds in helping with these post-disaster coordination projects in a short time span.

The Center for Global Development goes into more detail about how open data initiatives such as this and FAITH, the Philippine government's own Foreign Aid Transparency Hub launched 10 days after the crisis have played important roles already in helping to improve coordination and effectiveness.  

4. Local Knowledge is important:

We should bring data to local partners to critique and use in different ways, to allow them to make sense of it from their perspective. This point seemed to be about looking for more participatory and inclusive approaches to development using open data. It is a gap which early on was picked up by the UNDP. In this area the UNDP has pointed out the importance of creating channels for people’s voice within institutions in order to make them more responsive to the poor.

5. Think about goals:

Do we need to return to thinking about the goals of development rather than always talking about the means and the tools? If we are thinking about opening up development for the future, then for what and for who? Should we still be calling it development at all? Is using a framework and language of development helpful in terms of dealing with the problems of climate change, migration and systemic risk today? Or should we be attempting to subvert or re-cast those terms?

6. Don’t be a bubble:

Open data for development claims to be a potential force for good, but if it remains both mainstream and expert driven it may not evolve to close the widening gap between the highest levels and people who are the most disempowered and decision making at a local level. In terms of dialogue, we are still a little bubble. People find exciting ways to circumvent that insularity continuously, but unfortunately it is part of the DNA of open development that it lives in the hands of technical experts. Over time concerns such as building linguistic localisation, creating clear documentation, using simple language and searching for criticism and making openness a cultural watchword for how we operate, may need to be addressed more fully. The point was made that the open data movement is still relatively new and has only just emerged to find itself in the mainstream but from another perspective this problem is not at all new. A dependence on technical expertise, closed language and forms of knowledge has always featured heavily within technical communities and development communities alike.

Quick wins for open development in summary: 

- use local partners: they know their contexts best

- integrate with media sources to build on existing more popular media

- train each other to analyse data

- fill gaps in terms of standards and semantics

- call out institutions that do not make data interoperable

- remind governments of their commitments

- publish metadata and the methodology of what gets published

- share examples of what open data can change

- share failure and be open about what is not working

- be realistic about what the small community can solve. This movement is still fairly new

- allow people to tinker with data 

Further comments

Jay Naidoo, Chair of the Board of Directors and Chair of the Partnership Council of the Global Alliance for Improved Nutrition (GAIN) made a clear call in his keynote at OKCON in 2013 for open development to bring politics to the table, for a 'revolution of morality'. He urged us to think about the ethics, to think about how we mobilise citizens as whistleblowers and journalists, to think about ways to also bring about the progressive realisation of human rights through how we are using technology.

After the panel I decided to reflect on this call to action and to the idea of bringing politics in. How would you create tools to build a more caring and humane society that focuses more on the vulnerable? Where should politics be more involved in open development?

Political discussions about goals, mobilisation and even ethics are often separated from the discussions about standards, practices and 'lessons learned'. Since the High Level Panel's report on the Post-2015 agenda coined the phrase, the call for a 'data revolution' has been moderately anodyne. Open data work seems more focused on tools, distilling expertise in the manipulation, statistical calculation and collection of data than on the kinds of stories we are seeking to tell and to whom.

But I’d like to look at three reasons why it seems to me people should do more thinking about linking these seperate discussions together, at least in open development. I'd like to draw out some of these questions for people to wrangle with in the open community.

The first reason is that open data is not really seperate from existing reforms to public service delivery and governance. It could just be seen as the logical extension of other political reforms to decentralise government and decision making. Both the left and the right have their different ideas about this and tend to see different types of opportunities in decentralisation, and so also in 'openness'. For the left it is an opportunity to open channels for giving voice and bringing processes closer to the people, while for the right it appeals because it opens up accountability measures and short-cuts, providing opportunities for improved efficiency and cost savings. It can sit politically within a 'third way' approach. But either way, it will need to fit in clearly with the designs of politics in any given context.

The second reason is that it is implicitly a challenge to the status quo from the 'outside'. A dynamic of innovation seems to be building on these new insider / outsider relationships. Decision making is concentrated in the hands of those that hold power, experience and wisdom. The proof of which is in their embodiment of assets such as knowledge and networks, implicitly shaping discourse. The mainstream if you like is geared powerfully towards sustaining and protecting all that it has created, and less towards change and the new. In contrast the relatively fragile, emergent and innovative solutions adopted by outsiders and different actors are partly designed to disrupt this. There are always ‘early adopters’ of change, and a necessary and sufficient point of convergence for change. To be clear if the 'data revolution' is about a change process and innovation, handing power over in order to bring about change, then within this process there will always be different pathways and circles driving it.

But the point here was to be critical. Providing critiques of open data initiatives is a necessary and essential part of stirring the pot in a process of evaluation and reflection. Bringing attention to the fact that there are different understandings and versions of 'open data' out there is healthy and opens pathways to improve what people do. This debate between Rob Kitchin and David Eaves is one example.  

It is worth mentioning the wonderful opportunity to learn from others, particularly by reflecting on what stands at the heart of being 'open’ for different communities and where that leads to. One definition proposed by Mitchell Baker, Executive Chair of the Mozilla Foundation, to me highlights the potential for innovation and problem solving. 

She suggests that by building things in a way that they are inherently interoperable, we have the opportunity to try new things and so we can do more. By documenting and making things knowable and transparent, we can see them and understand them, so we can know more. When we do more and know more, she suggests there are many other things we can do better. The hope might be for development that this will foster and build accountability and trustworthiness, and individual choice and empowerment. Openness is a mission that the open movement is passionate about and is very good at. The good news is that there is real expertise to build on and learn from everywhere within this movement. The work of Open Matt on openness at Mozilla for example, is a shining demonstration of this.

Thirdly, this seems to me to be political because the future of development work itself is at something of a turning point. Development work in the future is likely to be different, possibly requiring different kinds of political agreements between new and old donors, emerging middle income and lower income countries. At the same time that we are discussing new priorities for development, some donor countries such as Australia and Canada are locking down their bilateral aid agencies, while others are heralding the end of the golden age of NGO's, or limiting their funding for example in Kenya. Many governments seem to be keen to 'leave room' for wider and leaner action by the private sector or initiatives driven by corporate social responsibility.

The point here is to highlight the danger of simply debating the tools and the means, without getting clear about where we are going and how. Planning for the future is also a process of working backwards from a vision. But there are some quite different versions of that vision out there at this current time.

Nancy Birdsall for one, sees this as a simple and straightforward leap towards the end of aid and development altogether by 2030. However, her ideas detailed in her blog post '2030 ODA No More' stand in contrast to those placing greater importance on tackling inequality (see the Guardian's debate on this or the IPS). Other perspectives such as that of Amartya Sen from the capability perspective, are aiming for a more human centered and rights based model for development. To be clear, there are likely to be at least as many different understandings of ‘open development’ as there are of ‘openness’ and ‘development’ alone.

Finally, calling something ‘open’ doesn’t just make it so. Development is a discourse that has a history spanning over many years. It is a world in which global institutions largely have been able to impose policy and change from above. The servicing of debt to global lenders with structural adjustment policies throughout the 90’s for example was imposed on countries in the process of fostering 'modern institutions, democracy and economic growth' in the process of ‘development’. It also led to the imposition of many destructive policies. 

The simple fact of encouraging participation of different voices and ideas now does not simply lead to all voices counting equally. Participation and openness are not the same thing either. As Tiago Peixoto points out in his piece on experiments with participatory budgeting, participation is always unequal. We should consider inclusiveness in our approach to ‘openness’, promoting the participation of previously marginalized sectors of society. The amplification of networked and distributed decision making alone does not undo the fact that power is overly concentrated in the hands of a few. It may simply mean that those who control such networks have a mechanism through which to speak for the multitude across a new architecture of interconnected nodes with greater complexity and power. 

Or as Ruth Carlitz suggests, is participation really being encouraged or is it simply a framework for ‘being participated with’. Surely our standards for ‘openness’ have to take into account in the end whether the dynamic suggests real participation or not? And to what extent might this dynamic be reflected within global transparency initiatives? For example while governments in many countries have been encouraged to become more 'open' about their budgets and their aid giving, the global lenders at the IMF score comparatively poorly on ‘openness’ and are not yet IATI signatories.

Without bringing attention to some of the political issues, efforts to widen decentralised governance and accountability through ‘openness’ will not take into account the political questions highlighted in the points above. That is to say, how such a process gains traction from both the left and the right in any context within political institutions, how it implicitly articulates itself as a challenge to the status quo, and finally how it conceives of goals and leads towards a vision for the future in order to confront problems such as widening inequality, financial risk and unmitigated climate change. ‘Participation’ in short is not enough, it simply renders this 'openness' in the weakest sense.

Tiago Peixoto has also pointed out that transparency projects are also often the “low-hanging fruit” of open governance, and are tempting for governments to focus on. His work has questioned the simplicity with which notions of participation and participatory experiments have been thought to lead directly to more effective collective action. Without a definition of ‘openness’ in development that also considers political barriers explicitly, that also encompasses barriers to collective action, there is a real sense that this ‘openness’ serves partly to isolate and close off aspects of this area of decision making from view. What remains outside of our own definitions of ‘open development’ should concern us, or we may end up refashioning development for its own purposes more than for anyone else's.