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Abstract

Mobile phone data have been extensively used to study urban mobility. However, studies based on gender-disaggregated large-scale data are still lacking, limiting our understanding of gendered aspects of urban mobility and our ability to design policies for gender equality. Here we study urban mobility from a gendered perspective, combining commercial and open datasets for the city of Santiago, Chile. We analyze call detail records for a large cohort of anonymized mobile phone users and reveal a gender gap in mobility: women visit fewer unique locations than men, and distribute their time less equally among such locations. Mapping this mobility gap over administrative divisions, we observe that a wider gap is associated with lower income and lack of public and private transportation options. Our results uncover a complex interplay between gendered mobility patterns, socioeconomic factors and urban affordances, calling for further research and providing insights for policymakers and urban planners.

Recent years have witnessed considerable speculation about the potential of open data to bring about wide-scale transformation. The bulk of existing evidence about the impact of open data, however, focuses on high-income countries. Much less is known about open data's role and value in low- and middle-income countries, and more generally about its possible contributions to economic and social development. Open Data for Developing Economies features in-depth case studies on how open data is having an impact across the developing world-from an agriculture initiative in Colombia to data-driven healthcare projects in Uganda and South Africa to crisis response in Nepal. The analysis built on these case studies aims to create actionable intelligence regarding: (a) the conditions under which open data is most (and least) effective in development, presented in the form of a Periodic Table of Open Data; (b) strategies to maximize the positive contributions of open data to development; and (c) the means for limiting open data's harms on developing countries.

Every era faces a unique set of challenges and dilemmas, but ours can credibly lay claim to some of the most complex and vexing that humankind may have ever confronted. From climate change to growing inequality to a rising tide of refugees: we face an intricate mesh of overlapping and interdependent difficulties, one that is pushing the limits of our existing policy and governance capabilities (Data for Policy, 2015; Meyer et al., 2017). What we require today are not so much (or not only) new solutions, but new ways for arriving at solutions (Susha et al., 2017). We need a twenty-first century paradigm of governance and policy making. Data, it is increasingly clear, will be central to this paradigm (Pentland, 2013; Kirkpatrick, 2012). Along with ever increasing computer storage and analytics capabilities, massive amounts of data generated from citizens, devices, and sensors provide decision makers the opportunity to monitor and manage public infrastructure in real time and predict future patterns when used responsibly (Engin and Treleaven, 2019; Janssen and Helbig, 2018). Data have the potential to transform every part of the policy-making life cycle-agenda setting and needs identification; the search for solutions; prototyping and implementation of solutions; enforcement; and evaluation (Janssen and Helbig, 2018). These are all critical, interlinked steps in addressing our societal challenges, and each of these needs a radical rethink. The idea that data could be a key differentiator is, of course, not a new one. Its potential has been evident for some time now (Wang et al., 2018), especially in the business world (Henke et al., 2016), but also in the policy community, where efforts to harness the power of information have yielded positive results in areas as disparate as gender equality (Fatehkia et al., 2018), improving urban traffic flows (Zhao et al., 2018), and enhancing regulatory compliance (Heat Seek, n.d.; Credit Suisse, n.d.). Successful data initiatives have been deployed by governments around the world in both developing and developed countries (Verhulst and Young, 2017a). Such initiatives have led to a growing recognition that data are and should increasingly be part of any effective governance toolkit. Despite such encouraging results, it is true that the policy world has generally lagged behind business in its use of data and data methods (Hou et al., 2011). Policy-data interactions or governance initiatives that use data have been the exception rather than the norm, isolated prototypes and trials rather than an indication of real, systemic change. There are various reasons for the generally slow uptake of data in policymaking, and several factors will have to change if the situation is to improve. In particular, advocates of more data (and we include ourselves among this number) will need to overcome the following obstacles and limitations: • Despite the number of successful prototypes and small-scale initiatives, policy makers' understanding of data's potential and its value proposition generall...

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