Data-Intensive Approaches To Creating Innovation For Sustainable Smart Cities


Science Trends: “Located at the complex intersection of economic development and environmental change, cities play a central role in our efforts to move towards sustainability. Reducing air and water pollution, improving energy efficiency while securing energy supply, and minimizing vulnerabilities to disruptions and disturbances are interconnected and pose a formidable challenge, with their dynamic interactions changing in highly complex and unpredictable manners….

The Beijing City Lab demonstrates the usefulness of open urban data in mapping urbanization with a fine spatiotemporal scale and reflecting social and environmental dimensions of urbanization through visualization at multiple scales.

The basic principle of open data will generate significant opportunities for promoting inter-disciplinary and inter-organizational research, producing new data sets through the integration of different sources, avoiding duplication of research, facilitating the verification of previous results, and encouraging citizen scientists and crowdsourcing approaches. Open data also is expected to help governments promote transparency, citizen participation, and access to information in policy-making processes.

Despite a significant potential, however, there still remain numerous challenges in facilitating innovation for urban sustainability through open data. The scope and amount of data collected and shared are still limited, and the quality control, error monitoring, and cleaning of open data is also indispensable in securing the reliability of the analysis. Also, the organizational and legal frameworks of data sharing platforms are often not well-defined or established, and it is critical to address the interoperability between various data standards, balance between open and proprietary data, and normative and legal issues such as the data ownership, personal privacy, confidentiality, law enforcement, and the maintenance of public safety and national security….

These findings are described in the article entitled Facilitating data-intensive approaches to innovation for sustainability: opportunities and challenges in building smart cities, published in the journal Sustainability Science. This work was led by Masaru Yarime from the City University of Hong Kong….(More)”.

Selected Readings on Data, Gender, and Mobility


By Michelle Winowatan, Andrew Young, and Stefaan Verhulst

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data, gender, and mobility was originally published in 2017.

This edition of the Selected Readings was  developed as part of an ongoing project at the GovLab, supported by Data2X, in collaboration with UNICEF, DigitalGlobe, IDS (UDD/Telefonica R&D), and the ISI Foundation, to establish a data collaborative to analyze unequal access to urban transportation for women and girls in Chile. We thank all our partners for their suggestions to the below curation – in particular Leo Ferres at IDS who got us started with this collection; Ciro Cattuto and Michele Tizzoni from the ISI Foundation; and Bapu Vaitla at Data2X for their pointers to the growing data and mobility literature. 

Introduction

Daily mobility is key for gender equity. Access to transportation contributes to women’s agency and independence. The ability to move from place to place safely and efficiently can allow women to access education, work, and the public domain more generally. Yet, mobility is not just a means to access various opportunities. It is also a means to enter the public domain.

Women’s mobility is a multi-layered challenge
Women’s daily mobility, however, is often hampered by social, cultural, infrastructural, and technical barriers. Cultural bias, for instance, limits women mobility in a way that women are confined to an area with close proximity to their house due to society’s double standard on women to be homemakers. From an infrastructural perspective, public transportation mostly only accommodates home-to-work trips, when in reality women often make more complex trips with stops, for example, at the market, school, healthcare provider – sometimes called “trip chaining.” From a safety perspective, women tend to avoid making trips in certain areas and/or at certain time, due to a constant risk of being sexually harassed on public places. Women are also pushed toward more expensive transportation – such as taking a cab instead of a bus or train – based on safety concerns.

The growing importance of (new sources of) data
Researchers are increasingly experimenting with ways to address these interdependent problems through the analysis of diverse datasets, often collected by private sector businesses and other non-governmental entities. Gender-disaggregated mobile phone records, geospatial data, satellite imagery, and social media data, to name a few, are providing evidence-based insight into gender and mobility concerns. Such data collaboratives – the exchange of data across sectors to create public value – can help governments, international organizations, and other public sector entities in the move toward more inclusive urban and transportation planning, and the promotion of gender equity.
The below curated set of readings seek to focus on the following areas:

  1. Insights on how data can inform gender empowerment initiatives,
  2. Emergent research into the capacity of new data sources – like call detail records (CDRs) and satellite imagery – to increase our understanding of human mobility patterns, and
  3. Publications exploring data-driven policy for gender equity in mobility.

Readings are listed in alphabetical order.

We selected the readings based upon their focus (gender and/or mobility related); scope and representativeness (going beyond one project or context); type of data used (such as CDRs and satellite imagery); and date of publication.

Annotated Reading List

Data and Gender

Blumenstock, Joshua, and Nathan Eagle. Mobile Divides: Gender, Socioeconomic Status, and Mobile Phone Use in Rwanda. ACM Press, 2010.

  • Using traditional survey and mobile phone operator data, this study analyzes gender and socioeconomic divides in mobile phone use in Rwanda, where it is found that the use of mobile phones is significantly more prevalent in men and the higher class.
  • The study also shows the differences in the way men and women use phones, for example: women are more likely to use a shared phone than men.
  • The authors frame their findings around gender and economic inequality in the country to the end of providing pointers for government action.

Bosco, Claudio, et al. Mapping Indicators of Female Welfare at High Spatial Resolution. WorldPop and Flowminder, 2015.

  • This report focuses on early adolescence in girls, which often comes with higher risk of violence, fewer economic opportunity, and restrictions on mobility. Significant data gaps, methodological and ethical issues surrounding data collection for girls also create barriers for policymakers to create evidence-based policy to address those issues.
  • The authors analyze geolocated household survey data, using statistical models and validation techniques, and creates high-resolution maps of various sex-disaggregated indicators, such as nutrition level, access to contraception, and literacy, to better inform local policy making processes.
  • Further, it identifies the gender data gap and issues surrounding gender data collection, and provides arguments for why having a comprehensive data can help create better policy and contribute to the achievements of the Sustainable Development Goals (SDGs).

Buvinic, Mayra, Rebecca Furst-Nichols, and Gayatri Koolwal. Mapping Gender Data Gaps. Data2X, 2014.

  • This study identifies gaps in gender data in developing countries on health, education, economic opportunities, political participation, and human security issues.
  • It recommends ways to close the gender data gap through censuses and micro-level surveys, service and administrative records, and emphasizes how “big data” in particular can fill the missing data that will be able to measure the progress of women and girls well being. The authors argue that dentifying these gaps is key to advancing gender equality and women’s empowerment, one of the SDGs.

Catalyzing Inclusive FInancial System: Chile’s Commitment to Women’s Data. Data2X, 2014.

  • This article analyzes global and national data in the banking sector to fill the gap of sex-disaggregated data in Chile. The purpose of the study is to describe the difference in spending behavior and priorities between women and men, identify the challenges for women in accessing financial services, and create policies that promote women inclusion in Chile.

Ready to Measure: Twenty Indicators for Monitoring SDG Gender Targets. Open Data Watch and Data2X, 2016.

  • Using readily available data this study identifies 20 SDG indicators related to gender issues that can serve as a baseline measurement for advancing gender equality, such as percentage of women aged 20-24 who were married or in a union before age 18 (child marriage), proportion of seats held by women in national parliament, and share of women among mobile telephone owners, among others.

Ready to Measure Phase II: Indicators Available to Monitor SDG Gender Targets. Open Data Watch and Data2X, 2017.

  • The Phase II paper is an extension of the Ready to Measure Phase I above. Where Phase I identifies the readily available data to measure women and girls well-being, Phase II provides informations on how to access and summarizes insights from this data.
  • Phase II elaborates the insights about data gathered from ready to measure indicators and finds that although underlying data to measure indicators of women and girls’ wellbeing is readily available in most cases, it is typically not sex-disaggregated.
  • Over one in five – 53 out of 232 – SDG indicators specifically refer to women and girls. However, further analysis from this study reveals that at least 34 more indicators should be disaggregated by sex. For instance, there should be 15 more sex-disaggregated indicators for SDG number 3: “Ensure healthy lives and promote well-being for all at all ages.”
  • The report recommends national statistical agencies to take the lead and assert additional effort to fill the data gap by utilizing tools such as the statistical model to fill the current gender data gap for each of the SDGs.

Reed, Philip J., Muhammad Raza Khan, and Joshua Blumenstock. Observing gender dynamics and disparities with mobile phone metadata. International Conference on Information and Communication Technologies and Development (ICTD), 2016.

  • The study analyzes mobile phone logs of millions of Pakistani residents to explore whether there is a difference in mobile phone usage behavior between male and female and determine the extent to which gender inequality is reflected in mobile phone usage.
  • It utilizes mobile phone data to analyze the pattern of usage behavior between genders, and socioeconomic and demographic data obtained from census and advocacy groups to assess the state of gender equality in each region in Pakistan.
  • One of its findings is a strong positive correlation between proportion of female mobile phone users and education score.

Stehlé, Juliette, et al. Gender homophily from spatial behavior in a primary school: A sociometric study. 2013.

    • This paper seeks to understand homophily, a human behavior characterizes by interaction with peers who have similarities in “physical attributes to tastes or political opinions”. Further, it seeks to identify the magnitude of influence, a type of homophily has to social structures.
    • Focusing on gender interaction among primary school aged children in France, this paper collects data from wearable devices from 200 children in the period of 2 days and measure the physical proximity and duration of the interaction among those children in the playground.
  • It finds that interaction patterns are significantly determined by grade and class structure of the school. Meaning that children belonging to the same class have most interactions, and that lower grades usually do not interact with higher grades.
  • From a gender lens, this study finds that mixed-gender interaction lasts shorter relative to same-gender interaction. In addition, interaction among girls is also longer compared to interaction among boys. These indicate that the children in this school tend to have stronger relationships within their own gender, or what the study calls gender homophily. It further finds that gender homophily is apparent in all classes.

Data and Mobility

Bengtsson, Linus, et al. Using Mobile Phone Data to Predict the Spatial Spread of Cholera. Flowminder, 2015.

  • This study seeks to predict the 2010 cholera epidemic in Haiti using 2.9 million anonymous mobile phone SIM cards and reported cases of Cholera from the Haitian Directorate of Health, where 78 study areas were analyzed in the period of October 16 – December 16, 2010.
  • From this dataset, the study creates a mobility matrix that indicates mobile phone movement from one study area to another and combines that with the number of reported case of cholera in the study areas to calculate the infectious pressure level of those areas.
  • The main finding of its analysis shows that the outbreak risk of a study area correlates positively with the infectious pressure level, where an infectious pressure of over 22 results in an outbreak within 7 days. Further, it finds that the infectious pressure level can inform the sensitivity and specificity of the outbreak prediction.
  • It hopes to improve infectious disease containment by identifying areas with highest risks of outbreaks.

Calabrese, Francesco, et al. Understanding Individual Mobility Patterns from Urban Sensing Data: A Mobile Phone Trace Example. SENSEable City Lab, MIT, 2012.

  • This study compares mobile phone data and odometer readings from annual safety inspections to characterize individual mobility and vehicular mobility in the Boston Metropolitan Area, measured by the average daily total trip length of mobile phone users and average daily Vehicular Kilometers Traveled (VKT).
  • The study found that, “accessibility to work and non-work destinations are the two most important factors in explaining the regional variations in individual and vehicular mobility, while the impacts of populations density and land use mix on both mobility measures are insignificant.” Further, “a well-connected street network is negatively associated with daily vehicular total trip length.”
  • This study demonstrates the potential for mobile phone data to provide useful and updatable information on individual mobility patterns to inform transportation and mobility research.

Campos-Cordobés, Sergio, et al. “Chapter 5 – Big Data in Road Transport and Mobility Research.” Intelligent Vehicles. Edited by Felipe Jiménez. Butterworth-Heinemann, 2018.

  • This study outlines a number of techniques and data sources – such as geolocation information, mobile phone data, and social network observation – that could be leveraged to predict human mobility.
  • The authors also provide a number of examples of real-world applications of big data to address transportation and mobility problems, such as transport demand modeling, short-term traffic prediction, and route planning.

Lin, Miao, and Wen-Jing Hsu. Mining GPS Data for Mobility Patterns: A Survey. Pervasive and Mobile Computing vol. 12,, 2014.

  • This study surveys the current field of research using high resolution positioning data (GPS) to capture mobility patterns.
  • The survey focuses on analyses related to frequently visited locations, modes of transportation, trajectory patterns, and placed-based activities. The authors find “high regularity” in human mobility patterns despite high levels of variation among the mobility areas covered by individuals.

Phithakkitnukoon, Santi, Zbigniew Smoreda, and Patrick Olivier. Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data. PLoS ONE, 2012.

  • This study used a year’s call logs and location data of approximately one million mobile phone users in Portugal to analyze the association between individuals’ mobility and their social networks.
  • It measures and analyze travel scope (locations visited) and geo-social radius (distance from friends, family, and acquaintances) to determine the association.
  • It finds that 80% of places visited are within 20 km of an individual’s nearest social ties’ location and it rises to 90% at 45 km radius. Further, as population density increases, distance between individuals and their social networks decreases.
  • The findings in this study demonstrates how mobile phone data can provide insights to “the socio-geography of human mobility”.

Semanjski, Ivana, and Sidharta Gautama. Crowdsourcing Mobility Insights – Reflection of Attitude Based Segments on High Resolution Mobility Behaviour Data. vol. 71, Transportation Research, 2016.

  • Using cellphone data, this study maps attitudinal segments that explain how age, gender, occupation, household size, income, and car ownership influence an individual’s mobility patterns. This type of segment analysis is seen as particularly useful for targeted messaging.
  • The authors argue that these time- and space-specific insights could also provide value for government officials and policymakers, by, for example, allowing for evidence-based transportation pricing options and public sector advertising campaign placement.

Silveira, Lucas M., et al. MobHet: Predicting Human Mobility using Heterogeneous Data Sources. vol. 95, Computer Communications , 2016.

  • This study explores the potential of using data from multiple sources (e.g., Twitter and Foursquare), in addition to GPS data, to provide a more accurate prediction of human mobility. This heterogenous data captures popularity of different locations, frequency of visits to those locations, and the relationships among people who are moving around the target area. The authors’ initial experimentation finds that the combination of these sources of data are demonstrated to be more accurate in identifying human mobility patterns.

Wilson, Robin, et al. Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake. PLOS Current Disasters, 2016.

  • Utilizing call detail records of 12 million mobile phone users in Nepal, this study seeks spatio-temporal details of the population after the earthquake on April 25, 2015.
  • It seeks to answer the problem of slow and ineffective disaster response, by capturing near real-time displacement pattern provided by mobile phone call detail records, in order to inform humanitarian agencies on where to distribute their assistance. The preliminary results of this study were available nine days after the earthquake.
  • This project relies on the foundational cooperation with mobile phone operator, who supplied the de-identified data from 12 million users, before the earthquake.
  • The study finds that shortly after the earthquake there was an anomalous population movement out of the Kathmandu Valley, the most impacted area, to surrounding areas. The study estimates 390,000 people above normal had left the valley.

Data, Gender and Mobility

Althoff, Tim, et al. “Large-Scale Physical Activity Data Reveal Worldwide Activity Inequality.” Nature, 2017.

  • This study’s analysis of worldwide physical activity is built on a dataset containing 68 million days of physical activity of 717,527 people collected through their smartphone accelerometers.
  • The authors find a significant reduction in female activity levels in cities with high active inequality, where high active inequality is associated with low city walkability – walkability indicators include pedestrian facilities (city block length, intersection density, etc.) and amenities (shops, parks, etc.).
  • Further, they find that high active inequality is associated with high levels of inactivity-related health problems, like obesity.

Borker, Girija. “Safety First: Street Harassment and Women’s Educational Choices in India.” Stop Street Harassment, 2017.

  • Using data collected from SafetiPin, an application that allows user to mark an area on a map as safe or not, and Safecity, another application that lets users share their experience of harassment in public places, the researcher analyzes the safety of travel routes surrounding different colleges in India and their effect on women’s college choices.
  • The study finds that women are willing to go to a lower ranked college in order to avoid higher risk of street harassment. Women who choose the best college from their set of options, spend an average of $250 more each year to access safer modes of transportation.

Frias-Martinez, Vanessa, Enrique Frias-Martinez, and Nuria Oliver. A Gender-Centric Analysis of Calling Behavior in a Developing Economy Using Call Detail Records. Association for the Advancement of Articial Intelligence, 2010.

  • Using encrypted Call Detail Records (CDRs) of 10,000 participants in a developing economy, this study analyzes the behavioral, social, and mobility variables to determine the gender of a mobile phone user, and finds that there is a difference in behavioral and social variables in mobile phone use between female and male.
  • It finds that women have higher usage of phone in terms of number of calls made, call duration, and call expenses compared to men. Women also have bigger social network, meaning that the number of unique phone numbers that contact or get contacted is larger. It finds no statistically significant difference in terms of distance made between calls in men and women.
  • Frias-Martinez et al recommends to take these findings into consideration when designing a cellphone based service.

Psylla, Ioanna, Piotr Sapiezynski, Enys Mones, Sune Lehmann. “The role of gender in social network organization.” PLoS ONE 12, December 20, 2017.

  • Using a large dataset of high resolution data collected through mobile phones, as well as detailed questionnaires, this report studies gender differences in a large cohort. The researchers consider mobility behavior and individual personality traits among a group of more than 800 university students.
  • Analyzing mobility data, they find both that women visit more unique locations over time, and that they have more homogeneous time distribution over their visited locations than men, indicating the time commitment of women is more widely spread across places.

Vaitla, Bapu. Big Data and the Well-Being of Women and Girls: Applications on the Social Scientific Frontier. Data2X, Apr. 2017.

  • In this study, the researchers use geospatial data, credit card and cell phone information, and social media posts to identify problems–such as malnutrition, education, access to healthcare, mental health–facing women and girls in developing countries.
  • From the credit card and cell phone data in particular, the report finds that analyzing patterns of women’s spending and mobility can provide useful insight into Latin American women’s “economic lifestyles.”
  • Based on this analysis, Vaitla recommends that various untraditional big data be used to fill gaps in conventional data sources to address the common issues of invisibility of women and girls’ data in institutional databases.

A Guide to Chicago’s Array of Things Initiative


Sean Thornton at Data-Smart City Solutions: “The 606, Chicago’s rails-to-trails project that stretches for 4.2 miles on the city’s northwest side, has been popular with residents and visitors ever since its launch last year.  The trail recently added a new art installationBlue Sky, that will greet visitors over the next five years with an array of lights and colors. Less noticed, but no less important, will be another array on display near the trail: a sensor node from Chicago’s Array of Things initiative.

If you’re a frequent reader of all things civic tech, then you may have already come across the Array of Things (AoT).  Launched in 2016, the project, which consists of a network of sensor boxes mounted on light posts, has now begun collecting a host of real-time data on Chicago’s environmental surroundings and urban activity.   After installing a small number of sensors downtown and elsewhere in 2016, Chicago is now adding additional sensors across the city and the city’s data portal currently lists locations for all of AoT’s active and yet-to-be installed sensors.  This year, data collected from AoT will be accessible online, providing valuable information for researchers, urban planners, and the general public.

AoT’s public engagement campaign has been picking up steam as well, with a recent community event held this fall. As a non-proprietary project, AoT is being implemented as a tool to improve not just urban planning and sustainability efforts, but quality of life for residents and communities. To engage with the public, project leaders have held meetings and workshops to build relationships with residents and identify community priorities. Those priorities, which vary from community to community, could range from monitoring traffic congestion around specific intersections to addressing air quality concerns at local parks and schoolyards.

The AoT project is a leading example of how new technology—and the Internet of Things (IoT) in particular—is transforming efforts for sustainable urban growth and “smart” city planning.  AoT’s truly multi-dimensional character sets it apart from other smart city efforts: complementing environmental sensor data collection, the initiative includes educational programming, community outreach, and R&D opportunities for academics, startups, corporations, and other organizations that could stand to benefit.

Launching a project like AoT, of course, isn’t as simple as installing sensor nodes and flipping on a switch. AoT has been in the works for years, and its recent launch marks a milestone event for its developers, the City of Chicago, and smart city technologies.  AoT has frequently appeared in the press  – yet often, coverage loses sight of the many facets of this unique project. How did AoT get to where it is today?  What is the project’s significance outside of Chicago? What are AoT’s implications for cities? Consider this article as your primer for all things AoT….(More)”.

Do-it-yourself science is taking off


The Economist: “…Citizen science has been around for ages—professional astronomers, geologists and archaeologists have long had their work supplemented by enthusiastic amateurs—and new cheap instruments can usefully spread the movement’s reach. What is more striking about bGeigie and its like, though, is that citizens and communities can use such instruments to inform decisions on which science would otherwise be silent—or mistrusted. For example, getting hold of a bGeigie led some people planning to move home after Fukushima to decide they were safer staying put.

Ms Liboiron’s research at CLEAR also stresses self-determination. It is subject to “community peer review”: those who have participated in the lab’s scientific work decide whether it is valid and merits publication. In the 1980s fishermen had tried to warn government scientists that stocks were in decline. Their cries were ignored and the sudden collapse of Newfoundland’s cod stocks in 1992 had left 35,000 jobless. The people taking science into their own hands with Ms Liboiron want to make sure that in the future the findings which matter to them get heard.

Swell maps

Issues such as climate change, plastic waste and air pollution become more tangible to those with the tools in their hands to measure them. Those tools, in turn, encourage more people to get involved. Eymund Diegel, a South African urban planner who is also a keen canoeist, has long campaigned for the Gowanus canal, close to his home in Brooklyn, to be cleaned up. Effluent from paint manufacturers, tanneries, chemical plants and more used to flow into the canal with such profligacy that by the early 20th century the Gowanus was said to be jammed solid. The New York mob started using the waterway as a dumping ground for dead bodies. In the early part of this century it was still badly polluted.

In 2009 Mr Diegel contacted Public Lab, an NGO based in New Orleans that helps people investigate environmental concerns. They directed him to what became his most powerful weapon in the fight—a mapping rig consisting of a large helium balloon, 300 metres (1,000 feet) of string and an old digital camera. A camera or smartphone fixed to such a balloon can take more detailed photographs than the satellite imagery used by the likes of Google for its online maps, and Public Lab provides software, called MapKnitter, that can stitch these photos together into surveys.

These data—and community pressure—helped persuade the Environmental Protection Agency (EPA) to make the canal eligible for money from a “superfund” programme which targets some of America’s most contaminated land. Mr Diegel’s photos have revealed a milky plume flowing into the canal from a concealed chemical tank which the EPA’s own surveys had somehow missed. The agency now plans to spend $500m cleaning up the canal….(More)”.

Innovation Contests: How to Engage Citizens in Solving Urban Problems?


Chapter by Sarah Hartmann, Agnes Mainka and Wolfgang G. Stock in Enhancing Knowledge Discovery and Innovation in the Digital Era: “Cities all over the world are challenged with problems evolving from increasing urbanity, population growth, and density. For example, one prominent issue that is addressed in many cities is mobility. To develop smart city solutions, governments are trying to introduce open innovation. They have started to open their governmental and city related data as well as awake the citizens’ awareness on urban problems through innovation contests.

Citizens are the users of the city and therefore, have a practical motivation to engage in innovation contests as for example in hackathons and app competitions. The collaboration and co-creation of civic services by means of innovation contests is a cultural development of how governments and citizens work together in an open governmental environment. A qualitative analysis of innovation contests in 24 world cities reveals this global trend. In particular, such events increase the awareness of citizens and local businesses for identifying and solving urban challenges and are helpful means to transfer the smart city idea into practicable solutions….(More)”.

Algorithms can deliver public services, too


Diane Coyle in the Financial Times: “As economists have been pointing out for a while, the combination of always-online smartphones and matching algorithms (of the kind pioneered by Nobel Prize-winning economist Richard Thaler and others) reduces the transaction costs involved in economic exchanges. As Ronald Coase argued, transaction costs, because they limit the scope of exchanges in the market, help explain why companies exist. Where those costs are high, it is more efficient to keep the activities inside an organisation. The relevant costs are informational. But in dense urban markets the new technologies make it easy and fast to match up the two sides of a desired exchange, such as a would-be passenger and a would-be driver for a specific journey. This can expand the market (as well as substituting for existing forms of transport such as taxis and buses). It becomes viable to serve previously under-served areas, or for people to make journeys they previously could not have afforded. In principle all parties (customers, drivers and platform) can share the benefits.

Making more efficient use of assets such as cars is nice, but the economic gains come from matching demand with supply in contexts where there are no or few economies of scale — such as conveying a passenger or a patient from A to B, or providing a night’s accommodation in a specific place.

Rather than being seen as a threat to public services, the new technologies should be taken as a compelling opportunity to deliver inherently unscalable services efficiently, especially given the fiscal squeeze so many authorities are facing. Public transport is one opportunity. How else could cash-strapped transportation authorities even hope to provide a universal service on less busy routes? It is hard to see why they should not make contractual arrangements with private providers. Nor is there any good economic reason they could not adopt the algorithmic matching model themselves, although the organisational effort might defeat many.

However, in ageing societies the big prize will be organising other services such as adult social care this way. These are inherently person to person and there are few economies of scale. The financial pressures on governments in delivering care are only going to grow. Adopting a more efficient model for matching demand and supply is so obvious a possible solution that pilot schemes are under way in several cities — both public sector-led and private start-ups. In fact, if public authorities do not try new models, the private sector will certainly fill the gap….(More)”.

Code and Clay, Data and Dirt: Five Thousand Years of Urban Media


Book by Shannon Mattern: “For years, pundits have trumpeted the earthshattering changes that big data and smart networks will soon bring to our cities. But what if cities have long been built for intelligence, maybe for millennia? In Code and Clay, Data and Dirt Shannon Mattern advances the provocative argument that our urban spaces have been “smart” and mediated for thousands of years.

Offering powerful new ways of thinking about our cities, Code and Clay, Data and Dirt goes far beyond the standard historical concepts of origins, development, revolutions, and the accomplishments of an elite few. Mattern shows that in their architecture, laws, street layouts, and civic knowledge—and through technologies including the telephone, telegraph, radio, printing, writing, and even the human voice—cities have long negotiated a rich exchange between analog and digital, code and clay, data and dirt, ether and ore.

Mattern’s vivid prose takes readers through a historically and geographically broad range of stories, scenes, and locations, synthesizing a new narrative for our urban spaces. Taking media archaeology to the city’s streets, Code and Clay, Data and Dirt reveals new ways to write our urban, media, and cultural histories….(More)”.

Participatory budgeting: adoption and transformation


Paper by Michael Touchton and Brian Wampler: “Participatory budgeting programmes are spreading rapidly across the world because they offer government officials and citizens the opportunity to engage each other in new ways as they combine democratic practices with the ‘nitty gritty’ of policy-making. The principles and ideas associated with participatory budgeting appeal to a broad spectrum of citizens, civil society activists, government officials and international agencies, which helps explain why it is so popular and has expanded so quickly.

In this research briefing, we focus on adoption and transformation of participatory budgeting in several low- and middle-income countries where international donors are active. We are particularly interested in better understanding how participatory budgeting is transforming in countries where international donors are active, where states struggle to provide public services, and where urban and rural communities are characterised by high levels of poverty… (More)”.

MOPA: How an app generates data that help clean-up Maputo


Making All Voices Count: “Maputo has a population of over 1.1 million people, with 54 per cent living below the poverty line and 70 per cent living in informal settlements. The majority of the city’s roads are unpaved and flood control is limited, particularly in informal settlements in peri-urban areas. During the rainy season, streets flood and gutters quickly fill with debris and garbage, blocking the drainage of rainwater.

Solid waste management is one of the most important services that the Maputo Municipal Council must provide. However the lack of funding, capacity, and transparency within the municipality has resulted in substandard waste removal.

The municipality has contracted private companies to collect the waste from the urban communities. Micro-entrepreneurs are hired to travel by foot through high-density, low-income areas using trolleys to pick up trash from households and communal bins in the peri-urban neighborhoods.

Both the waste removal companies and individual waste collectors have difficulties locating waste for removal, coordinating their routes and organising collection points.

MOPA – a tool for both citizens and local government

MOPA is a communications platform that allows participatory monitoring of waste collection in Maputo. Once a waste management problem is reported, one of two large waste collection companies and 56 micro-enterprises act to resolve it. Their actions are logged on the platform by Maputo’s municipality staff.

Implemented by the private company UX Information Technologies and co-designed with the Maputo Municipal Waste Management Services, the platform was initially supported by the World Bank.

With funding from Making All Voices Count, the platform expanded to 42 neighbourhoods (from the four pilot areas) and managed to include a free-to-user mobile application that can be used on any cellphone device with USSD and SMS alternatives. This change enabled residents to directly notify the municipality of problems, track their resolution, and get updates on when and how their issue has been addressed…(More)”.

Participatory Budgeting: Does Evidence Match Enthusiasm?


Brian Wampler, Stephanie McNulty, and Michael Touchton at Open Government Partnership: “Participatory budgeting (PB) empowers citizens to allocate portions of public budgets in a way that best fits the needs of the people. In turn, proponents expect PB to improve citizens’ lives in important ways, by expanding their participation in politics, providing better public services such as in healthcare, sanitation, or education, and giving them a sense of efficacy.

Below we outline several potential outcomes that emerge from PB. Of course, assessing PB’s potential impact is difficult, because reliable data is rare and PB is often one of several programs that could generate similar improvements at the same time. Impact evaluations for PB are thus at a very early stage. Nevertheless, considerable case study evidence and some broader, comparative studies point to outcomes in the following areas:

Citizens’ attitudes: Early research focused on the attitudes of citizens who participate in PB, and found that PB participants feel empowered, support democracy, view the government as more effective, and better understand budget and government processes after participating (Wampler and Avritzer 2004; Baiocchi 2005; Wampler 2007).

Participants’ behavior: Case-study evidence shows that PB participants increase their political participation beyond PB and join civil society groups. Many scholars also expect PB to strengthen civil society by increasing its density (number of groups), expanding its range of activities, and brokering new partnerships with government and other CSOs. There is some case study evidence that this occurs (Baiocchi 2005; McNulty 2011; Baiocchi, Heller and Silva 2011; Van Cott 2008) as well as evidence from over 100 PB programs across Brazil’s larger municipalities (Touchton and Wampler 2014). Proponents also expect PB to educate government officials surrounding community needs, to increase their support for participatory processes, and to potentially expand participatory processes in complementary areas. Early reports from five counties in Kenya suggest that PB ther is producing at least some of these impacts.

Electoral politics and governance: PB can also promote social change, which may alter local political calculations and the ways that governments operate. PB may deliver votes to the elected officials that sponsor it, improve budget transparency and resource allocation, decrease waste and fraud, and generally improve accountability. However, there is very little evidence in this area because few studies have been able to measure these impacts in any direct way.

Social well-being: Finally, PB is designed to improve residents’ well-being. Implemented PB projects include funding for healthcare centers, sewage lines, schools, wells, and other areas that contribute directly to well-being. These effects may take years to appear, but recent studies attribute improvements in infant mortality in Brazil to PB (Touchton and Wampler 2014; Gonçalves 2014). Beyond infant mortality, the range of potential impacts extends to other health areas, sanitation, education, and poverty in general. We are cautious here because results from Brazil might not appear elsewhere: what works in urban Brazil might not in rural Indonesia….(More)”.