Paper by Beatriz Botero Arcila: “Cities in the US have started to enact data-sharing rules and programs to access some of the data that technology companies operating under their jurisdiction – like short-term rental or ride hailing companies – collect. This information allows cities to adapt too to the challenges and benefits of the digital information economy. It allows them to understand what their impact is on congestion, the housing market, the local job market and even the use of public spaces. It also empowers them to act accordingly by, for example, setting vehicle caps or mandating a tailored minimum pay for gig-workers. These companies, however, sometimes argue that sharing this information attempts against their users’ privacy rights and their privacy rights, because this information is theirs; it’s part of their business records. The question is thus what those rights are, and whether it should and could be possible for local governments to access that information to advance equity and sustainability, without harming the legitimate privacy interests of both individuals and companies. This Article argues that within current Fourth Amendment doctrine and privacy law there is space for data-sharing programs. Privacy law, however, is being mobilized to alter the distribution of power and welfare between local governments, companies, and citizens within current digital information capitalism to extend those rights beyond their fair share and preempt permissible data-sharing requests. The Article warns that if the companies succeed in their challenges, privacy law will have helped shield corporate power from regulatory oversight, while still leaving individuals largely unprotected and submitting local governments further to corporate interests….(More)”.
Sustainable Cities: Big Data, Artificial Intelligence and the Rise of Green, “Cy-phy” Cities
Book by Claudio Scardovi: “Global cities are facing an almost unprecedented challenge of change. As they re-emerge from the Covid 19 pandemic and get ready to face climate change and other, potentially existential threats, they need to look for new ways to support wealth and wellbeing creation – leveraging Big Data and AI and suing them into their physical reality and to become greener, more inclusive and resilient, hence sustainable.This book describes how new digital technologies could be used to design digital and physical twins of cities that are able to feed into each other to optimize their working and ability to create new wealth and wellbeing. The book also describes how to increase cities’ social and economic resilience during crisis time and addressing their almost fatal weaknesses – as it became all too obvious during the recent COVID 19 crisis. Also, the book presents a framework for a critical discussion of the concept of “smart-city”, suggesting its development into a “cyber” and “meta” one – meaning, not only digital systems can allow physical ones (e.g. cities, citizens, households and companies) to become “smarter”, but also the vice versa is true, as off line data and real life behaviours can support the optimization and development of virtual brains as a sum of big data and artificial intelligence apps all sitting “over the cloud”.
An analysis of the fundamental dynamics of this emerging “info-telligence” economy, and of the potential role of big digital players like Amazon, Google and Facebook is then paving the way to discuss a few strategic forays on how traditional sectors such as financial services, real estate, TMT or health could also evolve, leveraging Big Data and AI in a cyber-physical integrated setting. Finally, a number of thought provoking use cases that could be designed around individuals, and to improve the success and the resilience of households and companies living and working in urban areas are discussed, as an example of one of the most exciting future markets to come: the one of global, sustainable cities…(More)”.
Using Open Data to Monitor the Status of a Metropolitan Area: The Case of the Metropolitan Area of Turin
Paper by Candela, Filippo; and Mulassano, Paolo: “The paper presents and discusses the method adopted by Compagnia di San Paolo, one of the largest European philanthropic institutions, to monitor the advancement, despite the COVID-19 situation, in providing specific input to the decision-making process for dedicated projects. An innovative approach based on the use of daily open data was adopted to monitor the metropolitan area with a multidimensional perspective. Several open data indicators related to the economy, society, culture, environment, and climate were identified and incorporated into the decision support system dashboard. Indicators are presented and discussed to highlight how open data could be integrated into the foundation’s strategic approach and potentially replicated on a large scale by local institutions. Moreover, starting from the lessons learned from this experience, the paper analyzes the opportunities and critical issues surrounding the use of open data, not only to improve the quality of life during the COVID-19 epidemic but also for the effective regulation of society, the participation of citizens, and their well-being….(More)”
Reimagining the Role of Cities & City Diplomacy in the Multilateral Order
Report by The Berggruen Institute: “The COVID-19 pandemic has brought to the foreground the important role of cities in responding to global challenges. Through informal and established international networks, city leaders are connecting across borders and shaping the global pandemic response. City and municipal governments were some of the earliest to turn toward their peers to share information, collaborate, and identify solutions, even as national-level cooperation was often delayed or challenged.
While the pandemic has revealed the necessity of international cooperation, it has also shown the limits of current systems, especially in how multilateral institutions learn from and meaningfully include city leadership. City and municipal governments occupy an increasingly visible and important position in international affairs, are already working together through city-to-city networks on many issues, and engage in international activities often described as “city diplomacy.” Looking forward, rapid population growth in urban areas means many global challenges and the responses to them will be concentrated in cities. Cities will be at the center of the global response to climate change, migration, violence and injustice, health security, economic inequality, and security. Yet the current international system was designed by countries for countries; it is not structured to channel city voices and lacks pathways for cities to influence global governance.
The Berggruen Institute, the Brookings Institution, the City of Los Angeles, and the United Nations Foundation co-organized a virtual workshop in July 2020 titled “The Rise of Urbanization and the Role of City Diplomacy in the Multilateral System” to explore these dynamics further. By bringing together current and former national diplomats, representatives of and diplomats in multilateral organizations, city directors of international affairs, and specialists in international relations under the Chatham House rule, the workshop aimed to reimagine how different levels of government can work together more effectively on issues of global governance. Together, these actors form a novel group to grapple with the issue of city voice in multilateralism. In particular, the group explored opportunities and challenges to building cooperation between cities and the current multilateral system and considered practical, researchable ideas for how the multilateral system might adapt to engage subnational actors to address global challenges….(More)”.
Sustainable mobility: Policy making for data sharing
WBCSD report: “The demand for mobility will grow significantly in the coming years, but our urban transportation systems are at their limits. Increasing digitalization and data sharing in urban mobility can help governments and businesses to respond to this challenge and accelerate the transition toward sustainability. There is an urgent need for greater policy coherence in data-sharing ecosystems and governments need to adopt a more collaborative approach toward policy making.
With well-orchestrated policies, data sharing can result in shared value for public and private sectors and support the achievement of sustainability goals. Data-sharing policies should also aim to minimize risks around privacy and cybersecurity, minimize mobility biases rooted in race, gender and age, prevent the creation of runaway data monopolies and bridge the widening data divide.
This report outlines a global policy framework and practical guidance for policy making on data sharing. The report offers multiple case studies from across the globe to document emerging good practices and policy suggestions, recognizing the hyperlocal context of mobility needs and policies, the nascent state of the data-sharing market and limited evidence from regulatory practices….(More)”
Building Digital Worlds: Where does GIS data come from?
Julie Stoner at Library of Congress: “Whether you’ve used an online map to check traffic conditions, a fitness app to track your jogging route, or found photos tagged by location on social media, many of us rely on geospatial data more and more each day. So what are the most common ways geospatial data is created and stored, and how does it differ from how we have stored geographic information in the past?
A primary method for creating geospatial data is to digitize directly from scanned analog maps. After maps are georeferenced, GIS software allows a data creator to manually digitize boundaries, place points, or define areas using the georeferenced map image as a reference layer. The goal of digitization is to capture information carefully stored in the original map and translate it into a digital format. As an example, let’s explore and then digitize a section of this 1914 Sanborn Fire Insurance Map from Eatonville, Washington.
Sanborn Fire Insurance Map from Eatonville, Pierce County, Washington. Sanborn Map Company, October 1914. Geography & Map Division, Library of Congress.
Sanborn Fire Insurance Maps were created to detail the built environment of American towns and cities through the late 19th and early 20th centuries. The creation of these information-dense maps allowed the Sanborn Fire Insurance Company to underwrite insurance agreements without needing to inspect each building in person. Sanborn maps have become incredibly valuable sources of historic information because of the rich geographic detail they store on each page.
When extracting information from analog maps, the digitizer must decide which features will be digitized and how information about those features will be stored. Behind the geometric features created through the digitization process, a table is utilized to store information about each feature on the map. Using the table, we can store information gleaned from the analog map, such as the name of a road or the purpose of a building. We can also quickly calculate new data, such as the length of a road segment. The data in the table can then be put to work in the visual display of the new digital information that has been created. This often done through symbolization and map labels….(More)”.
Establishment of Sustainable Data Ecosystems
Report and Recommendations for the evolution of spatial data infrastructures by S. Martin, Gautier, P., Turki, and S., Kotsev: “The purpose of this study is to identify and analyse a set of successful data ecosystems and to address recommendations that can act as catalysts of data-driven innovation in line with the recently published European data strategy. The work presented here tries to identify to the largest extent possible actionable items.
Specifically, the study contributes with insights into the approaches that would help in the evolution of existing spatial data infrastructures (SDI), which are usually governed by the public sector and driven by data providers, to self-sustainable data ecosystems where different actors (including providers, users, intermediaries.) contribute and gain social and economic value in accordance with their specific objectives and incentives.
The overall approach described in this document is based on the identification and documentation of a set of case studies of existing data ecosystems and use cases for developing applications based on data coming from two or more data ecosystems, based on existing operational or experimental applications. Following a literature review on data ecosystem thinking and modelling, a framework consisting of three parts (Annex I) was designed. An ecosystem summary is drawn, giving an overall representation of the ecosystem key aspects. Two additional parts are detailed. One dedicated to ecosystem value dynamic illustrating how the ecosystem is structured through the resources exchanged between stakeholders, and the associated value.
Consequently, the ecosystem data flows represent the ecosystem from a complementary and more technical perspective, representing the flows and the data cycles associated to a given scenario. These two parts provide good proxies to evaluate the health and the maturity of a data ecosystem…(More)”.
The Data Shake: Opportunities and Obstacles for Urban Policy Making
Book edited by Grazia Concilio, Paola Pucci, Lieven Raes and Geert Mareels: “This open access book represents one of the key milestones of PoliVisu, an H2020 research and innovation project funded by the European Commission under the call “Policy-development in the age of big data: data-driven policy-making, policy-modelling and policy-implementation”.
It investigates the operative and organizational implications related to the use of the growing amount of available data on policy making processes, highlighting the experimental dimension of policy making that, thanks to data, proves to be more and more exploitable towards more effective and sustainable decisions.
The first section of the book introduces the key questions highlighted by the PoliVisu project, which still represent operational and strategic challenges in the exploitation of data potentials in urban policy making. The second section explores how data and data visualisations can assume different roles in the different stages of a policy cycle and profoundly transform policy making….(More)”.
Selected Readings on Data, Gender, and Mobility
By Michelle Winowatan, Uma Kalkar, 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, and updated in 2021.
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’s 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 multiple 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 times due to a constant risk of being sexually harassed n 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:
- Insights on how data can inform gender empowerment initiatives,
- 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,
- 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 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 identifying these gaps is key to achieving SDG 5: advancing gender equality and women’s empowerment.
Catalyzing Inclusive Financial Systems: 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 information on how to access this data and summarizes insights extracted from it.
- 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 the 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 that characterizes interactions 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 applied 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 measures 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. This means 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.
Strengthening Gender Measures and Data in the COVID-19 Era: An Urgent Need for Change. Paris 21, 2021.
- COVID-19 has exacerbated gender disparities, especially with regard to women’s livelihoods, unpaid labor, mental health, and risk of gender-based violence. Gaps in gender data impedes robust, data-driven, and effective policies to quantify, analyse, and respond to these issues.
- Without this information, the full effects of the COVID-19 pandemic cannot be understood. This report calls on National Statistical Systems, survey managers, funders, multilateral agencies, researchers, and policymakers to collect gender-intentional and disaggregated data that is standardized and comparable to address key areas of concern for women and girls. Additionally, it seeks to link non-traditional data sources, such as social media and news media, with existing frameworks to fill in knowledge gaps. Moreover, this information must be rendered accessible for all stakeholders to maximize the potential of the information. Post-pandemic, conscious collection and collation of gendered data is vital to preempt policy problems.
The Sex, Gender and COVID-19 Project: The COVID-19 Sex-Disaggregated Data Tracker. 2021.
- This data tracker, produced by Global Health 50/50, the African Population and Health Research Center, and the International Center for Research on Women, tracks which countries and datasets have reported sex-disaggregated data on COVID-19 testing, confirmed cases, hospitalizations, and deaths.
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 cases 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.
Gauvin, Laetitia et al. Gender gaps in urban mobility. Humanities and Information Science. Humanities & Social Sciences Communications vol. 7, issue 11, 2020.
- This article discusses how urbanization affects mobility of women in realizing their rights. It points out the historic lack of gender disaggregated data for urban planning, leading to transportation designs that do not best accommodate the needs of women.
- Examining the case study of urban mobility through a gendered lens in the large and growing metropolitan area of Santiago, Chile, the article examines the mobility traces from Call Detail Records (CDRs) of an anonymized cohort of mobile phone users, sorted by gender, over 3 months. It then mapped differences between men and women with regard to socio-demographic indicators and mobility differences across the city and through the Santiago transportation network structure and identified points of interests frequented by either sex to inform gendered mobility needs in urban areas.
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 patterns 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 operators, 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 more people than 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 users 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, Borker 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 Artificial 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.
The Landscape of Big Data and Gender. Data2X, February, 2021.
- Under the backdrop of COVID-19, this report reaffirms that big data initiatives to study mobility, health, and social norms through gendered lenses have greatly progressed. More private companies and think tanks have launched data collection and sharing efforts to spur innovative projects to address COVID-19 complications.
- However, economic opportunity, security, and civic action have been lagging behind. Big data collection among these topics is complicated by the lack of sex-disaggregated datasets, gender disparities in technology access, and the lack of gender-tags among big data.
- Large technology firms, especially social networks like Facebook, LinkedIn, Uber, and more, create a large amount of gender-organized data. The report found that users and data-holding companies are willing to share this information for public policy reasons so long as it provides value and is protected. To this end, Data2X, alongside its partners, champion the use of data collaboratives to use gender sorted information for social good.
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.
Leveraging artificial intelligence to analyze citizens’ opinions on urban green space
Paper by Mohammadhossein Ghahramani, Nadina J.Galle, Fábio Duarte, Carlo Ratti, Francesco Pilla: “Continued population growth and urbanization is shifting research to consider the quality of urban green space over the quantity of these parks, woods, and wetlands. The quality of urban green space has been hitherto measured by expert assessments, including in-situ observations, surveys, and remote sensing analyses. Location data platforms, such as TripAdvisor, can provide people’s opinion on many destinations and experiences, including UGS. This paper leverages Artificial Intelligence techniques for opinion mining and text classification using such platform’s reviews as a novel approach to urban green space quality assessments. Natural Language Processing is used to analyze contextual information given supervised scores of words by implementing computational analysis. Such an application can support local authorities and stakeholders in their understanding of–and justification for–future investments in urban green space….(More)”.