Stefaan Verhulst

Interview with Galen Englund by Charlotte Alfred: “The U.N. Refugee Agency recently released its annual estimate of the world’s displaced population: 65.6 million. This figure is primarily based on data provided by governments, each using their own definitions and data collection methods.

This leaves ample space for inconsistencies and data gaps. South Africa, for example, reported 463,900 asylum seekers in 2014, 1.1 million in 2015 and then just 218,300 last year. But the number of people had not fluctuated that wildly. What did change was how asylum seekers are counted.

National estimates can also obscure entire groups of people, like internally displaced groups that governments don’t want to acknowledge, notes Galen Englund, who analyzes humanitarian data at the ONE Campaign advocacy organization.

Over the past year, Englund has been digging into the data on refugees and displaced populations for the ONE Campaign. It was an uphill battle. He collected figures from 67 reports that used 356 differently worded metrics in order to identify the needs of displaced populations. “Frequently information is not there, or it’s siloed within organizations, or there’s too much bureaucratic red tape around it, or it just hasn’t been collected yet,” he said.

His research resulted in a displacement tracking platform called Movement, which compiles various U.N. data, and a briefing paper outlining displacement data gaps that concludes: “The information architecture of humanitarian aid is not fit for purpose.” We spoke to Englund about his findings….

Galen Englund: There’s several layers of massive data gaps that all coincide with each other. Probably the most troubling for me is not being able to understand at a granular level where refugees and displaced people are inside of countries, and the transition between when someone leaves their home and becomes displaced, and when they actually cross international borders and become refugees or asylum seekers. That’s an incredibly difficult transition to track, and one that there’s inadequate data on right now….(More)”.

Jason Bradbury at the Office for National Statistics (UK): “Earlier this year we shared news about the Retail Sales Inquiry (RSI) – the monthly national survey of shops and shopping –  moving to digital data collection. ONS is transforming the way it collects data, improving the speed and quality of the information while reducing the burden on respondents. The past six months has seen a significant expansion of our digital survey availability. In January 5,000 retailers were invited to sign-up for an account giving them the option to send us their data  for one of our business surveys digitally.

Electronic questionnaires

The take-up of the electronic questionnaire (eQ) was incredible with over 80% of respondents choosing to supply their information for the RSI online. Overt the last six months, we have continued to see the appetite for online completion grow. Each month, an average of 300 new businesses opt to return their Retail Sales data digitally with many eager to move to digital methods for the other surveys they are required to complete….

Moving data collection from the phone and paper to online has been a huge success delivering improved quality, an ‘easy  to access’ online experience and when thinking about the impact this change could  have had on our core function as a statistical body, I am delighted to share that we have not witnessed any statistical issues and all of outputs have been compiled and produced as normal.

Put simply, the easier it is for someone to complete our surveys, the more likely they are to take the time to provide more detailed accurate data. It is worth noting that once a business has an account with ONS they often send back data to us quicker. The earlier and more detailed responses allow us more time to quality assure (QA) the information and reduce the need to re-contact the businesses.

Our digital journey

The digital world is a fast paced and an ever changing environment. We have found it challenging to match this pace in both our team’s skill base and our digital service. We are in the process of up-skilling our teams and updating our data collection service and infrastructure. This will enable us to improve our data collection service and move even more surveys online….(More)”

Hugh Byrd in The Conversation: “In 2014, the new Indian government declared its intention to achieve 100 smart cities.

In promoting this objective, it gave the example of a large development in the island city of Mumbai, Bhendi Bazaar. There, 3-5 storey housing would be replaced with towers of between 40 to 60 storeys to increase density. This has come to be known as “vertical with a vengeance”.

We have obtained details of the proposed project from the developer and the municipal authorities. Using an extended urban metabolism model, which measures the impacts of the built environment, we have assessed its overall impact. We determined how the flows of materials and energy will change as a result of the redevelopment.

Our research shows that the proposal is neither smart nor sustainable.

Measuring impacts

The Indian government clearly defined what they meant with “smart”. Over half of the 11 objectives were environmental and main components of the metabolism of a city. These include adequate water and sanitation, assured electricity, efficient transport, reduced air pollution and resource depletion, and sustainability.

We collected data from various primary and secondary sources. This included physical surveys during site visits, local government agencies, non-governmental organisations, the construction industry and research.

We then made three-dimensional models of the existing and proposed developments to establish morphological changes, including building heights, street widths, parking provision, roof areas, open space, landscaping and other aspects of built form.

Demographic changes (population density, total population) were based on census data, the developer’s calculations and an assessment of available space. Such information about the magnitude of the development and the associated population changes allowed us to analyse the additional resources required as well as the environmental impact….

Case studies such as Bhendi Bazaar provide an example of plans for increased density and urban regeneration. However, they do not offer an answer to the challenge of limited infrastructure to support the resource requirements of such developments.

The results of our research indicate significant adverse impacts on the environment. They show that the metabolism increases at a greater rate than the population grows. On this basis, this proposed development for Mumbai, or the other 99 cities, should not be called smart or sustainable.

With policies that aim to prevent urban sprawl, cities will inevitably grow vertically. But with high-rise housing comes dependence on centralised flows of energy, water supplies and waste disposal. Dependency in turn leads to vulnerability and insecurity….(More)”.

Sara Friedman at GCN: “As more local governments open their data for public use, the emphasis is often on “free” — using open source tools to freely share already-created government datasets, often with pro bono help from outside groups. But according to a new report, there are unforeseen costs when it comes pushing government datasets out of public-facing platforms — especially when geospatial data is involved.

The research, led by University of Waterloo professor Peter A. Johnson and McGill University professor Renee Sieber, was based on work as part of Geothink.ca partnership research grant and exploration of the direct and indirect costs of open data.

Costs related to data collection, publishing, data sharing, maintenance and updates are increasingly driving governments to third-party providers to help with hosting, standardization and analytical tools for data inspection, the researchers found. GIS implementation also has associated costs to train staff, develop standards, create valuations for geospatial data, connect data to various user communities and get feedback on challenges.

First, open data can create “smoke and mirrors” situation where insufficient resources are put toward deploying open data for government use. Users then experience “transaction costs” when it comes to working in specialist data formats that need additional skills, training and software to use.

Second, the level of investment and quality of open data can lead to “material benefits and social privilege” for communities that devote resources to providing more comprehensive platforms.

While there are some open source data platforms, the majority of solutions are proprietary and charged on a pro-rata basis, which can present a challenge for cities with larger, poor populations compared to smaller, wealthier cities. Issues also arise when governments try to combine their data sets, leading to increased costs to reconcile problems.

The third problem revolves around the private sector pushing for the release of data sets that can benefit their business objectives. Companies could push for the release high-value sets, such as a real-time transit data, to help with their product development goals. This can divert attention from low-value sets, such as those detailing municipal services or installations, that could have a bigger impact on residents “from a civil society perspective.”

If communities decide to release the low-value sets first, Johnson and Sieber think the focus can then be shifted to high-value sets that can help recoup the costs of developing the platforms.

Lastly, the report finds inadvertent consequences could result from tying open data resources to private-sector companies. Public-private open data partnerships could lead to infrastructure problems that prevent data from being widely shared, and help private companies in developing their bids for public services….

Johnson and Sieber encourage communities to ask the following questions before investing in open data:

1. Who are the intended constituents for this open data?
2. What is the purpose behind the structure for providing this data set?
3. Does this data enable the intended users to meet their goals?
4. How are privacy concerns addressed?
5. Who sets the priorities for release and updates?…(More)”

Read the full report here.

New Book by Jeanne Liedtka, Randy Salzman, and Daisy Azer:  “Facing especially wicked problems, social sector organizations are searching for powerful new methods to understand and address them. Design Thinking for the Greater Good goes in depth on both the how of using new tools and the why. As a way to reframe problems, ideate solutions, and iterate toward better answers, design thinking is already well established in the commercial world. Through ten stories of struggles and successes in fields such as health care, education, agriculture, transportation, social services, and security, the authors show how collaborative creativity can shake up even the most entrenched bureaucracies—and provide a practical roadmap for readers to implement these tools.

The design thinkers Jeanne Liedtka, Randy Salzman, and Daisy Azer explore how major agencies like the Department of Health and Human Services and the Transportation and Security Administration in the United States, as well as organizations in Canada, Australia, and the United Kingdom, have instituted principles of design thinking. In each case, these groups have used the tools of design thinking to reduce risk, manage change, use resources more effectively, bridge the communication gap between parties, and manage the competing demands of diverse stakeholders. Along the way, they have improved the quality of their products and enhanced the experiences of those they serve. These strategies are accessible to analytical and creative types alike, and their benefits extend throughout an organization. This book will help today’s leaders and thinkers implement these practices in their own pursuit of creative solutions that are both innovative and achievable….(More)”.

Asmus Leth Olsen at Public Management Review: “When faced with a problem, policymakers have a choice of action or inaction. Psychological research shows varying results on how individuals evaluate (in)actions conditional on the subsequent outcome. I replicate, generalize, and extend this research into a public management setting with two independent experiments embedded in a nationally representative sample of Danish citizens (n = 2,007).

Both experiments show that actions are evaluated more positively than inactions – regardless of the outcome. This finding runs contrary to the inaction (or omission) bias but is consistent with evidence on a “norm of action”, in response to poor performance in political–administrative settings….(More)”

Review by Lawrence Phillips, Chase Dowling, Kyle Shaffer, Nathan Hodas and Svitlana Volkov: “Social media (SM) data provides a vast record of humanity’s everyday thoughts, feelings, and actions at a resolution previously unimaginable. Because user behavior on SM is a reflection of events in the real world, researchers have realized they can use SM in order to forecast, making predictions about the future. The advantage of SM data is its relative ease of acquisition, large quantity, and ability to capture socially relevant information, which may be difficult to gather from other data sources. Promising results exist across a wide variety of domains, but one will find little consensus regarding best practices in either methodology or evaluation. In this systematic review, we examine relevant literature over the past decade, tabulate mixed results across a number of scientific disciplines, and identify common pitfalls and best practices. We find that SM forecasting is limited by data biases, noisy data, lack of generalizable results, a lack of domain-specific theory, and underlying complexity in many prediction tasks. But despite these shortcomings, recurring findings and promising results continue to galvanize researchers and demand continued investigation. Based on the existing literature, we identify research practices which lead to success, citing specific examples in each case and making recommendations for best practices. These recommendations will help researchers take advantage of the exciting possibilities offered by SM platforms….(More)”

Mujb Mashal the New York Times: “These are some of the terms Afghan men use to refer to their wives in public instead of their names, the sharing of which they see as a grave dishonor worthy of violence: Mother of Children, My Household, My Weak One or sometimes, in far corners, My Goat or My Chicken.

Women also may be called Milk-sharer or Black-headed. The go-to word for Afghans to call a woman in public, no matter her status, is Aunt.

But a social media campaign to change this custom has been percolating in recent weeks, initiated by young women. The campaign comes with a hashtag in local languages that addresses the core of the issue and translates as #WhereIsMyName.

The activists’ aim is both to challenge women to reclaim their most basic identity, and to break the deep-rooted taboo that prevents men from mentioning their female relatives’ names in public….

Like many social media efforts, this one began small, with several posts out of Herat Province in the west. Since then, more activists have tried to turn it into a topic of conversation by challenging celebrities and government officials to share the names of their wives and mothers.

The discussion has now made it to the regular media, with articles in newspapers and conversations on television and radio talk shows.

Members of the Parliament, senior government officials and artists have come forward in support, publicly declaring the identities of the female members of their families….(More)”

Paper by Rajan Vaish et al: “Research experiences today are limited to a privileged few at select universities. Providing open access to research experiences would enable global upward mobility and increased diversity in the scientific workforce. How can we coordinate a crowd of diverse volunteers on open-ended research? How could a PI have enough visibility into each person’s contributions to recommend them for further study? We present Crowd Research, a crowdsourcing technique that coordinates open-ended research through an iterative cycle of open contribution, synchronous collaboration, and peer assessment. To aid upward mobility and recognize contributions in publications, we introduce a decentralized credit system: participants allocate credits to each other, which a graph centrality algorithm translates into a collectively-created author order. Over 1,500 people from 62 countries have participated, 74% from institutions with low access to research. Over two years and three projects, this crowd has produced articles at top-tier Computer Science venues, and participants have gone on to leading graduate programs….(More)”.