The Governance of Digital Technology, Big Data, and the Internet: New Roles and Responsibilities for Business
Introduction to Special Issue of Business and Society by Dirk Matten, Ronald Deibert & Mikkel Flyverbom: “The importance of digital technologies for social and economic developments and a growing focus on data collection and privacy concerns have made the Internet a salient and visible issue in global politics. Recent developments have increased the awareness that the current approach of governments and business to the governance of the Internet and the adjacent technological spaces raises a host of ethical issues. The significance and challenges of the digital age have been further accentuated by a string of highly exposed cases of surveillance and a growing concern about issues of privacy and the power of this new industry. This special issue explores what some have referred to as the “Internet-industrial complex”—the intersections between business, states, and other actors in the shaping, development, and governance of the Internet…(More)”.
Using street imagery and crowdsourcing internet marketplaces to measure motorcycle helmet use in Bangkok, Thailand
Hasan S. Merali, Li-Yi Lin, Qingfeng Li, and Kavi Bhalla in Injury Prevention: “The majority of Thailand’s road traffic deaths occur on
Using Google Maps, 3000 intersections in Bangkok were selected at random. At each intersection, hyperlinks of four images 90° apart were extracted. These 12 000 images were processed in Amazon Mechanical Turk using crowdsourcing to identify images containing motorcycles. The remaining images were sorted manually to determine helmet use
After processing, 462 unique motorcycle drivers were
This novel method of estimating helmet use has produced results similar to traditional methods. Applying this technology can reduce
Identifying commonly used and potentially unsafe transit transfers with crowdsourcing
Paper by Elizabeth J.Traut and Aaron Steinfeld: “Public transit is an important contributor to sustainable transportation as well as a public service that makes necessary travel possible for many. Poor transit transfers can lead to both a real and perceived reduction in convenience and safety, especially for people with disabilities. Poor transfers can expose riders to inclement weather and crime, and they can reduce transit ridership by motivating riders who have the option of driving or using paratransit to elect a more expensive and inefficient travel mode. Unfortunately, knowledge about inconvenient, missed, and unsafe transit transfers is sparse and incomplete.
We show that crowdsourced public transit ridership data, which is more scalable than conducting traditional surveys, can be used to analyze transit transfers. The Tiramisu Transit app merges open transit data with information contributed by users about which trips they take. We use Tiramisu data to do origin-destination analysis and identify connecting trips to create a better understanding of where and when poor transfers are occurring in the Pittsburgh region. We merge the results with data from other open public data sources, including crime data, to create a data resource that can be used for planning and identification of locations where bus shelters and other infrastructure improvements may facilitate safer and more comfortable waits and more accessible transfers. We use generalizable methods to ensure broader value to both science and practitioners.
We present a case study of the Pittsburgh region, in which we identified and characterized 338 transfers from 142 users. We found that 66.6% of transfers were within 0.4 km (0.25 mi.) and 44.1% of transfers were less than 10 min. We identified the geographical distribution of transfers and found several highly-utilized transfer locations that were not identified by the Port Authority of Allegheny County as recommended transfer points, and so might need more planning attention. We cross-referenced transfer location and wait time data with crime levels to provide additional planning insight….(More)”.
Circular City Data

First Volume of Circular City, A Research Journal by New Lab edited by André Corrêa d’Almeida: “…Circular City Data is the topic being explored in the first iteration of New Lab’s The Circular City program, which looks at data and knowledge as the energy, flow, and medium of collaboration. Circular data refers to the collection, production, and exchange of data, and business insights, between a series of collaborators around a shared set of inquiries. In some scenarios, data may be produced by start-ups and of high value to the city; in other cases, data may be produced by the city and of potential value to the public, start-ups, or enterprise companies. The conditions that need to be in place to safely, ethically, and efficiently extrapolate the highest potential value from data are what this program aims to uncover.
Similar to living systems, urban systems can be enhanced if the total pool of data available, i.e., energy, can be democratized and decentralized and data analytics used widely to positively impact quality of life. The abundance of data available, the vast differences in capacity across organizations to handle it, and the growing complexity of urban challenges provides an opportunity to test how principles of circular city data can help establish new forms of public and private partnerships that make cities more economically prosperous, livable, and resilient. Though we talk of an overabundance of data, it is often still not visible or tactically wielded at the local level in a way that benefits people.
Circular City Data is an effort to build a safe environment whereby start-ups, city agencies, and larger firms can collect, produce, access and exchange data, as well as business insights, through transaction mechanisms that do not necessarily require currency, i.e., through reciprocity. Circular data is data that travels across a number of stakeholders, helping to deliver insights and make clearer the opportunities where such stakeholders can work together to improve outcomes. It includes cases where a set of “circular” relationships need to be in place in order to produce such data and business insights. For example, if an AI company lacks access to raw data from the city, they won’t be able to provide valuable insights to the city. Or, Numina required an established relationship with the DBP in order to access infrastructure necessary for them to install their product and begin generating data that could be shared back with them. ***
Next, the case study documents and explains how The Circular City program was conceived, designed, and implemented, with the goal of offering lessons for scalability at New Lab and replicability in other cities around the world. The three papers that follow investigate and methodologically test the value of circular data applied to three different, but related, urban challenges: economic growth, mobility, and resilience.
Contents
- Introduction to The Circular City Research Program (André Corrêa d’Almeida)
- The Circular City Program: The Case Study (André Corrêa d’Almeida and Caroline McHeffey)
- Circular Data for a Circular City: Value Propositions for Economic Development (Stefaan G. Verhulst, Andrew Young, and Andrew J. Zahuranec)
- Circular Data for a Circular City: Value Propositions for Mobility (Arnaud Sahuguet)
- Circular Data for a Circular City: Value Propositions for Resilience and Sustainability (Nilda Mesa)
Conclusio (André Corrêa d’Almeida)
The role of information and communications technology in the transformation of government and citizen trust
Mohamed Mahmood et al in the International Review of Administrative Sciences: “We present an empirically tested conceptual model based on
The tools of citizen science: An evaluation of map-based crowdsourcing platforms
Paper by Zachary Lamoureux and Victoria Fast: “There seems to be a persistent yet inaccurate sentiment that collecting vast amounts of data via citizen science is virtually free, especially compared to the cost of privatized scientific endeavors (Bonney et al., 2009; Cooper, Hochachka & Dhondt, 2011). However, performing scientific procedures with the assistance of the public is often far more complex than traditional scientific
Citizen science promotes the participation of the public in scientific endeavors (Hecker et al., 2018). While citizen science is not synonymous with volunteered geographic information (VGI)— broadly defined as the creation of geographic information by citizens (Goodchild, 2007)—it often produces geographic information. Similar to VGI, citizen science projects tend to follow specific protocols to ensure the crowdsourced geographic data serves as an input for (scientific) research (Haklay, 2013). Also similar to VGI, citizen science projects often require software applications and specialized training to facilitate citizen data collection. Notably, citizen science projects are increasingly requiring a
In this research, we investigate publicly available commercial and opensource map-based tools that enable citizen science projects. Building on a comprehensive comparative framework, we conduct a systematic evaluation and overview of five map-based crowdsourcing platforms: Ushahidi, Maptionnaire, Survey123 (ArcGIS Online), Open Data Kit, and GIS Cloud. These tools have additional uses that extend beyond the field of citizen science; however, the scope of the investigation was narrowed to focus on aspects most suitable for citizen science endeavors, such as the collection, management, visualization and dissemination of crowdsourced data. It is our intention to provide information on how these publicly available crowdsourcing platforms suit generic geographic citizen science crowdsourcing needs….(More)”.
A Review of Citizen Science and Crowdsourcing in Applications of Pluvial Flooding
Jonathan D. Paul in Frontiers in Earth Science: “Pluvial flooding can have devastating effects, both in terms of loss of life and damage. Predicting pluvial floods is difficult and many cities do not have a hydrodynamic model or an early warning system in place. Citizen science and crowdsourcing have the potential for contributing to early warning systems and can also provide data for validating flood forecasting models. Although there are increasing applications of citizen science and crowdsourcing in fluvial hydrology, less is known about activities related to pluvial flooding. Hence the aim of this paper is to review current activities in citizen science and crowdsourcing with respect to applications of pluvial flooding.
Based on a search in Scopus, the papers were first filtered for relevant content and then classified into four main themes. The first two themes were divided into (i) applications relevant during a flood event, which includes automated street flooding detection using crowdsourced photographs and sensors, analysis of social media, and online and mobile applications for flood reporting; and (ii) applications related to post-flood events. The use of citizen science and crowdsourcing for model development and validation is the third theme while the development of integrated systems is theme four. All four main areas of research have the potential to contribute to early warning systems and build community resilience. Moreover, developments in one will benefit others, e.g., further developments in flood reporting applications and automated flood detection systems will yield data useful for model validation….(More)”.
Big data needs big governance: best practices from Brain-CODE, the Ontario Brain Institute’s neuroinformatics platform
Shannon C. Lefaivre et al in Frontiers of Genetics: “The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants.
Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives….(More)”.
Information audit as an important tool in organizational management: A review of literature
Paper by Ayinde Lateef, Funmilola Olubunmi Omotayo: “This article considers information as a strategic asset in the organization just as land,