Selected Readings on Data Governance

Curated on Posted on by Jos Berens

Jos Berens (Centre for Innovation, Leiden University) and Stefaan G. Verhulst (GovLab)

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 governance was originally published in 2015.

Context
The field of Data Collaboratives is premised on the idea that sharing and opening-up private sector datasets has great – and yet untapped – potential for promoting social good. At the same time, the potential of data collaboratives depends on the level of societal trust in the exchange, analysis and use of the data exchanged. Strong data governance frameworks are essential to ensure responsible data use. Without such governance regimes, the emergent data ecosystem will be hampered and the (perceived) risks will dominate the (perceived) benefits. Further, without adopting a human-centered approach to the design of data governance frameworks, including iterative prototyping and careful consideration of the experience, the responses may fail to be flexible and targeted to real needs.

Selected Readings List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Better Place Lab, “Privacy, Transparency and Trust.” Mozilla, 2015. Available from: http://www.betterplace-lab.org/privacy-report.

  • This report looks specifically at the risks involved in the social sector having access to datasets, and the main risks development organizations should focus on to develop a responsible data use practice.
  • Focusing on five specific countries (Brazil, China, Germany, India and Indonesia), the report displays specific country profiles, followed by a comparative analysis centering around the topics of privacy, transparency, online behavior and trust.
  • Some of the key findings mentioned are:
    • A general concern on the importance of privacy, with cultural differences influencing conception of what privacy is.
    • Cultural differences determining how transparency is perceived, and how much value is attached to achieving it.
    • To build trust, individuals need to feel a personal connection or get a personal recommendation – it is hard to build trust regarding automated processes.

Montjoye, Yves Alexandre de; Kendall, Jake and; Kerry, Cameron F. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, 2015. Available from: http://www.brookings.edu/research/papers/2014/11/12-enabling-humanitarian-use-mobile-phone-data.

  • Focussing in particular on mobile phone data, this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
  • Key takeaways are the following recommendations for using data for social good:
    • Engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.
    • Accepting that no framework for maximizing data for the public good will offer perfect protection for privacy, but there must be a balanced application of privacy concerns against the potential for social good.
    • Establishing systems and processes for recognizing trusted third-parties and systems to manage datasets, enable detailed audits, and control the use of data so as to combat the potential for data abuse and re-identification of anonymous data.
    • Simplifying the process among developing governments in regards to the collection and use of mobile phone metadata data for research and public good purposes.

Centre for Democracy and Technology, “Health Big Data in the Commercial Context.” Centre for Democracy and Technology, 2015. Available from: https://cdt.org/insight/health-big-data-in-the-commercial-context/.

  • Focusing particularly on the privacy issues related to using data generated by individuals, this paper explores the overlap in privacy questions this field has with other data uses.
  • The authors note that although the Health Insurance Portability and Accountability Act (HIPAA) has proven a successful approach in ensuring accountability for health data, most of these standards do not apply to developers of the new technologies used to collect these new data sets.
  • For non-HIPAA covered, customer facing technologies, the paper bases an alternative framework for consideration of privacy issues. The framework is based on the Fair Information Practice Principles, and three rounds of stakeholder consultations.

Center for Information Policy Leadership, “A Risk-based Approach to Privacy: Improving Effectiveness in Practice.” Centre for Information Policy Leadership, Hunton & Williams LLP, 2015. Available from: https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/white_paper_1-a_risk_based_approach_to_privacy_improving_effectiveness_in_practice.pdf.

  • This white paper is part of a project aiming to explain what is often referred to as a new, risk-based approach to privacy, and the development of a privacy risk framework and methodology.
  • With the pace of technological progress often outstripping the capabilities of privacy officers to keep up, this method aims to offer the ability to approach privacy matters in a structured way, assessing privacy implications from the perspective of possible negative impact on individuals.
  • With the intended outcomes of the project being “materials to help policy-makers and legislators to identify desired outcomes and shape rules for the future which are more effective and less burdensome”, insights from this paper might also feed into the development of innovative governance mechanisms aimed specifically at preventing individual harm.

Centre for Information Policy Leadership, “Data Governance for the Evolving Digital Market Place”, Centre for Information Policy Leadership, Hunton & Williams LLP, 2011. Available from: http://www.huntonfiles.com/files/webupload/CIPL_Centre_Accountability_Data_Governance_Paper_2011.pdf.

  • This paper argues that as a result of the proliferation of large scale data analytics, new models governing data inferred from society will shift responsibility to the side of organizations deriving and creating value from that data.
  • It is noted that, with the reality of the challenge corporations face of enabling agile and innovative data use “In exchange for increased corporate responsibility, accountability [and the governance models it mandates, ed.] allows for more flexible use of data.”
  • Proposed as a means to shift responsibility to the side of data-users, the accountability principle has been researched by a worldwide group of policymakers. Tailing the history of the accountability principle, the paper argues that it “(…) requires that companies implement programs that foster compliance with data protection principles, and be able to describe how those programs provide the required protections for individuals.”
  • The following essential elements of accountability are listed:
    • Organisation commitment to accountability and adoption of internal policies consistent with external criteria
    • Mechanisms to put privacy policies into effect, including tools, training and education
    • Systems for internal, ongoing oversight and assurance reviews and external verification
    • Transparency and mechanisms for individual participation
    • Means of remediation and external enforcement

Crawford, Kate; Schulz, Jason. “Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm.” NYU School of Law, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&download=yes.

  • Considering the privacy implications of large-scale analysis of numerous data sources, this paper proposes the implementation of a ‘procedural data due process’ mechanism to arm data subjects against potential privacy intrusions.
  • The authors acknowledge that some privacy protection structures already know similar mechanisms. However, due to the “inherent analytical assumptions and methodological biases” of big data systems, the authors argue for a more rigorous framework.

Letouze, Emmanuel, and; Vinck, Patrick. “The Ethics and Politics of Call Data Analytics”, DataPop Alliance, 2015. Available from: http://static1.squarespace.com/static/531a2b4be4b009ca7e474c05/t/54b97f82e4b0ff9569874fe9/1421442946517/WhitePaperCDRsEthicFrameworkDec10-2014Draft-2.pdf.

  • Focusing on the use of Call Detail Records (CDRs) for social good in development contexts, this whitepaper explores both the potential of these datasets – in part by detailing recent successful efforts in the space – and political and ethical constraints to their use.
  • Drawing from the Menlo Report Ethical Principles Guiding ICT Research, the paper explores how these principles might be unpacked to inform an ethics framework for the analysis of CDRs.

Data for Development External Ethics Panel, “Report of the External Ethics Review Panel.” Orange, 2015. Available from: http://www.d4d.orange.com/fr/content/download/43823/426571/version/2/file/D4D_Challenge_DEEP_Report_IBE.pdf.

  • This report presents the findings of the external expert panel overseeing the Orange Data for Development Challenge.
  • Several types of issues faced by the panel are described, along with the various ways in which the panel dealt with those issues.

Federal Trade Commission Staff Report, “Mobile Privacy Disclosures: Building Trust Through Transparency.” Federal Trade Commission, 2013. Available from: www.ftc.gov/os/2013/02/130201mobileprivacyreport.pdf.

  • This report looks at ways to address privacy concerns regarding mobile phone data use. Specific advise is provided for the following actors:
    • Platforms, or operating systems providers
    • App developers
    • Advertising networks and other third parties
    • App developer trade associations, along with academics, usability experts and privacy researchers

Mirani, Leo. “How to use mobile phone data for good without invading anyone’s privacy.” Quartz, 2015. Available from: http://qz.com/398257/how-to-use-mobile-phone-data-for-good-without-invading-anyones-privacy/.

  • This paper considers the privacy implications of using call detail records for social good, and ways to mitigate risks of privacy intrusion.
  • Taking example of the Orange D4D challenge and the anonymization strategy that was employed there, the paper describes how classic ‘anonymization’ is often not enough. The paper then lists further measures that can be taken to ensure adequate privacy protection.

Bernholz, Lucy. “Several Examples of Digital Ethics and Proposed Practices” Stanford Ethics of Data conference, 2014, Available from: http://www.scribd.com/doc/237527226/Several-Examples-of-Digital-Ethics-and-Proposed-Practices.

  • This list of readings prepared for Stanford’s Ethics of Data conference lists some of the leading available literature regarding ethical data use.

Abrams, Martin. “A Unified Ethical Frame for Big Data Analysis.” The Information Accountability Foundation, 2014. Available from: http://www.privacyconference2014.org/media/17388/Plenary5-Martin-Abrams-Ethics-Fundamental-Rights-and-BigData.pdf.

  • Going beyond privacy, this paper discusses the following elements as central to developing a broad framework for data analysis:
    • Beneficial
    • Progressive
    • Sustainable
    • Respectful
    • Fair

Lane, Julia; Stodden, Victoria; Bender, Stefan, and; Nissenbaum, Helen, “Privacy, Big Data and the Public Good”, Cambridge University Press, 2014. Available from: http://www.dataprivacybook.org.

  • This book treats the privacy issues surrounding the use of big data for promoting the public good.
  • The questions being asked include the following:
    • What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens?
    • What are the rules of engagement?
    • What are the best ways to provide access while protecting confidentiality?
    • Are there reasonable mechanisms to compensate citizens for privacy loss?

Richards, Neil M, and; King, Jonathan H. “Big Data Ethics”. Wake Forest Law Review, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2384174.

  • This paper describes the growing impact of big data analytics on society, and argues that because of this impact, a set of ethical principles to guide data use is called for.
  • The four proposed themes are: privacy, confidentiality, transparency and identity.
  • Finally, the paper discusses how big data can be integrated into society, going into multiple facets of this integration, including the law, roles of institutions and ethical principles.

OECD, “OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data”. Available from: http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm.

  • A globally used set of principles to inform thought about handling personal data, the OECD privacy guidelines serve as one the leading standards for informing privacy policies and data governance structures.
  • The basic principles of national application are the following:
    • Collection Limitation Principle
    • Data Quality Principle
    • Purpose Specification Principle
    • Use Limitation Principle
    • Security Safeguards Principle
    • Openness Principle
    • Individual Participation Principle
    • Accountability Principle

The White House Big Data and Privacy Working Group, “Big Data: Seizing Opportunities, Preserving Values”, White House, 2015. Available from: https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf.

  • Documenting the findings of the White House big data and privacy working group, this report lists i.a. the following key recommendations regarding data governance:
    • Bringing greater transparency to the data services industry
    • Stimulating international conversation on big data, with multiple stakeholders
    • With regard to educational data: ensuring data is used for the purpose it is collected for
    • Paying attention to the potential for big data to facilitate discrimination, and expanding technical understanding to stop discrimination

William Hoffman, “Pathways for Progress” World Economic Forum, 2015. Available from: http://www3.weforum.org/docs/WEFUSA_DataDrivenDevelopment_Report2015.pdf.

  • This paper treats i.a. the lack of well-defined and balanced governance mechanisms as one of the key obstacles preventing particularly corporate sector data from being shared in a controlled space.
  • An approach that balances the benefits against the risks of large scale data usage in a development context, building trust among all stake holders in the data ecosystem, is viewed as key.
  • Furthermore, this whitepaper notes that new governance models are required not just by the growing amount of data and analytical capacity, and more refined methods for analysis. The current “super-structure” of information flows between institutions is also seen as one of the key reasons to develop alternatives to the current – outdated – approaches to data governance.

Five Headlines from a Big Month for the Data Revolution

Curated on Posted on by Stefaan Verhulst

Sarah T. Lucas at Post2015.org: “If the history of the data revolution were written today, it would include three major dates. May 2013, when theHigh Level Panel on the Post-2015 Development Agenda first coined the phrase “data revolution.” November 2014, when the UN Secretary-General’s Independent Expert Advisory Group (IEAG) set a vision for it. And April 2015, when five headliner stories pushed the data revolution from great idea to a concrete roadmap for action.

The April 2015 Data Revolution Headlines

1. The African Data Consensus puts Africa in the lead on bringing the data revolution to the regional level. TheAfrica Data Consensus (ADC) envisions “a profound shift in the way that data is harnessed to impact on development decision-making, with a particular emphasis on building a culture of usage.” The ADC finds consensus across 15 “data communities”—ranging from open data to official statistics to geospatial data, and is endorsed by Africa’s ministers of finance. The ADC gets top billing in my book, as the first contribution that truly reflects a large diversity of voices and creates a political hook for action. (Stay tuned for a blog from my colleague Rachel Quint on the ADC).

2. The Sustainable Development Solutions Network (SDSN) gets our minds (and wallets) around the data needed to measure the SDGs. The SDSN Needs Assessment for SDG Monitoring and Statistical Capacity Development maps the investments needed to improve official statistics. My favorite parts are the clear typology of data (see pg. 12), and that the authors are very open about the methods, assumptions, and leaps of faith they had to take in the costing exercise. They also start an important discussion about how advances in information and communications technology, satellite imagery, and other new technologies have the potential to expand coverage, increase analytic capacity, and reduce the cost of data systems.

3. The Overseas Development Institute (ODI) calls on us to find the “missing millions.” ODI’s The Data Revolution: Finding the Missing Millions presents the stark reality of data gaps and what they mean for understanding and addressing development challenges. The authors highlight that even that most fundamental of measures—of poverty levels—could be understated by as much as a quarter. And that’s just the beginning. The report also pushes us to think beyond the costs of data, and focus on how much good data can save. With examples of data lowering the cost of doing government business, the authors remind us to think about data as an investment with real economic and social returns.

4. Paris21 offers a roadmap for putting national statistic offices (NSOs) at the heart of the data revolution.Paris21’s Roadmap for a Country-Led Data Revolution does not mince words. It calls on the data revolution to “turn a vicious cycle of [NSO] underperformance and inadequate resources into a virtuous one where increased demand leads to improved performance and an increase in resources and capacity.” It makes the case for why NSOs are central and need more support, while also pushing them to modernize, innovate, and open up. The roadmap gets my vote for best design. This ain’t your grandfather’s statistics report!

5. The Cartagena Data Festival features real-live data heroes and fosters new partnerships. The Festival featured data innovators (such as terra-i using satellite data to track deforestation), NSOs on the leading edge of modernization and reform (such as Colombia and the Philippines), traditional actors using old data in new ways (such as the Inter-American Development Bank’s fantastic energy database), groups focused on citizen-generated data (such as The Data Shift and UN My World), private firms working with big data for social good (such asTelefónica), and many others—all reminding us that the data revolution is well underway and will not be stopped. Most importantly, it brought these actors together in one place. You could see the sparks flying as folks learned from each other and hatched plans together. The Festival gets my vote for best conference of a lifetime, with the perfect blend of substantive sessions, intense debate, learning, inspiration, new connections, and a lot of fun. (Stay tuned for a post from my colleague Kristen Stelljes and me for more on Cartagena).

This month full of headlines leaves no room for doubt—momentum is building fast on the data revolution. And just in time.

With the Financing for Development (FFD) conference in Addis Ababa in July, the agreement of Sustainable Development Goals in New York in September, and the Climate Summit in Paris in December, this is a big political year for global development. Data revolutionaries must seize this moment to push past vision, past roadmaps, to actual action and results…..(More)”

New surveys reveal dynamism, challenges of open data-driven businesses in developing countries

Curated on Posted on by Stefaan Verhulst

Alla Morrison at World Bank Open Data blog: “Was there a class of entrepreneurs emerging to take advantage of the economic possibilities offered by open data, were investors keen to back such companies, were governments tuned to and responsive to the demands of such companies, and what were some of the key financing challenges and opportunities in emerging markets? As we began our work on the concept of an Open Fund, we partnered with Ennovent (India), MDIF (East Asia and Latin America) and Digital Data Divide (Africa) to conduct short market surveys to answer these questions, with a focus on trying to understand whether a financing gap truly existed in these markets. The studies were fairly quick (4-6 weeks) and reached only a small number of companies (193 in India, 70 in Latin America, 63 in South East Asia, and 41 in Africa – and not everybody responded) but the findings were fairly consistent.

  • Open data is still a very nascent concept in emerging markets. and there’s only a small class of entrepreneurs/investors that is aware of the economic possibilities; there’s a lot of work to do in the ‘enabling environment’
    • In many regions the distinction between open data, big data, and private sector generated/scraped/collected data was blurry at best among entrepreneurs and investors (some of our findings consequently are better indicators of  data-driven rather than open data-driven businesses)
  • There’s a small but growing number of open data-driven companies in all the markets we surveyed and these companies target a wide range of consumers/users and are active in multiple sectors
    • A large percentage of identified companies operate in sectors with high social impact – health and wellness, environment, agriculture, transport. For instance, in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low-income population or the rural segment of India as an intended beneficiary segment. In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture. In Southeast Asia, business, consumer services, and transport came out in the lead.
    • We found the highest number of companies in Latin America and Asia with the following countries leading the way – Mexico, Chile, and Brazil, with Colombia and Argentina closely behind in Latin America; and India, Indonesia, Philippines, and Malaysia in Asia
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia
    • We heard demand for different kinds of financing (equity, debt, working capital) but the majority of the need was for equity and quasi-equity in amounts ranging from $100,000 to $5 million USD, with averages of between $2 and $3 million USD depending on the region.
  • There’s a significant financing gap in all the markets
    • The investment sizes required, while they range up to several million dollars, are generally small. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million
  • Venture capitals generally don’t recognize data as a separate sector and club data-driven companies with their standard information communication technology (ICT) investments
    • Interviews with founders suggest that moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment.
    • From the perspective of startups, investors favor banal e-commerce (e.g., according toTech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators. The space is ripe for a long-term investor with a generous risk appetite and multiple bottom line goals.
  • Poor data quality was the number one issue these companies reported.
    • Companies reported significant waste and inefficiency in accessing/scraping/cleaning data.

The analysis below borrows heavily from the work done by the partners. We should of course mention that the findings are provisional and should not be considered authoritative (please see the section on methodology for more details)….(More).”

Twitter for government: Indonesians get social media for public services

Curated on Posted on by Stefaan Verhulst

Medha Basu at FutureGov: “One of the largest users of social media in the world, Indonesians are taking it a step further with a new social network just for public services.

Enda Nasution and his team have built an app called Sebangsa, or Same Nation, featuring Facebook-like timelines (or Twitter-like feeds) for citizens to share about public services.

They want to introduce an idea they call “social government” in Indonesia, Nasution told FutureGov, going beyond e-government and open government to build a social relationship between the government and citizens….

It has two features that stand out. One called Sebangsa911 is for Indonesians to post emergencies, much like they might on Twitter or Facebook when they see an accident on the road or a crowd getting violent, for instance. Indonesia does not have any single national emergency number.

Another feature is called Sebangsa1800 which is a channel for people to post reviews, questions and complaints on public services and consumer products.

Why another social network?
But why build another social network when there are millions of users on Facebook and Twitter already? One reason is to provide a service that focuses on Indonesians, Nasution said – the app is in Bahasa.

Another is because existing social networks are not built specifically for public services. If you post a photo of an accident on Twitter, how many and how fast people see it depends on how many followers you have, Nasution said. These reports are also unstructured because they are “scattered all over Twitter”, he said. The app “introduces a little bit of structure to the reports”….(More)”

New portal to crowdsource captions, transcripts of old photos, national archives

Curated on Posted on by Stefaan Verhulst
Irene Tham at The Straits Times: “Wanted: history enthusiasts to caption old photographs and transcribe handwritten manuscripts that contain a piece of Singapore’s history.

They are invited to contribute to an upcoming portal that will carry some 3,000 unidentified photographs dating back to the late 1800s, and 3,000 pages of Straits Settlement records including letters written during Sir Stamford Raffles’ administration of Singapore.

These are collections from the Government and individuals waiting to be “tagged” on the new portal – The Citizen Archivist Project at www.nas.gov.sg/citizenarchivist….

Without tagging – such as by photo captioning and digital transcription – these records cannot be searched. There are over 140,000 photos and about one million pages of Straits Settlements Records in total that cannot be searched today.

These records date back to the 1800s, and include letters written during Sir Stamford Raffles’ administration in Singapore.

“The key challenge is that they were written in elaborate cursive penmanship which is not machine-readable,” said Dr Yaacob, adding that the knowledge and wisdom of the public can be tapped on to make these documents more accessible.

Mr Arthur Fong (West Coast GRC) had asked how the Government could get young people interested in history, and Dr Yaacob said this initiative was something they would enjoy.

Portal users must first log in using their existing Facebook, Google or National Library Board accounts. Contributions will be saved in users’ profiles, automatically created upon signing in.

Transcript contributions on the portal work in similar ways to Wikipedia; contributed text will be uploaded immediately on the portal.

However, the National Archives will take up to three days to review photo caption contributions. Approved captions will be uploaded on its website at www.nas.gov.sg/archivesonline….(More)”

2015 Edelman Trust Barometer

Curated on Posted on by Stefaan Verhulst
“The 2015 Edelman Trust Barometer shows a global decline in trust over the last year, and the number of countries with trusted institutions has fallen to an all-time low among the informed public.

Among the general population, the trust deficit is even more pronounced, with nearly two-thirds of countries falling into the distruster category.
In the last year, trust has declined for three of the four institutions measured. NGOs continue to be the most trusted institution, but trust in NGOs declined from 66 to 63 percent. Sixty percent of countries now distrust media. Trust in government increased slightly, driven by big gains in India, Russia and Indonesia but government is still distrusted in 19 of the 27 markets surveyed. And trust in business is below 50 percent in half of those markets.
 

The downside of Open Data

Curated on Posted on by Stefaan Verhulst

Joshua Chambers at FutureGov: “…Inaccurate public datasets can cause big problems, because apps that feed off of them could be giving out false information. I was struck by this when we reported on an app in Australia that was issuing alerts for forest fires that didn’t exist. The data was coming from public emergency calls, but wasn’t verified before being displayed. This meant that app users would be alerted of all possible fires, but also could be caused unnecessarily panic. The government takes the view that more alerts are better than slower verified ones, but there is the potential for people to become less likely to trust all alerts on the app.
No-one wants to publish inaccurate data, but accuracy takes time and costs money. So we come to a central tension in discussions about open data: is it better to publish more data, with the risk of inaccuracy, or limit publication to datasets which are accurate?
The United Kingdom takes the view that more data is best. I interviewed the UK’s lead official on open data, Paul Maltby, a couple of years ago, and he told me that: “There’s a misnomer here that everything has to be perfect before you can put it out,” adding that “what we’re finding is that, actually, some of the datasets are a bit messy. We try to keep them as high-quality as we can; but other organisations then clean up the data and sell it on”.
Indeed, he noted that some officials use data accuracy as an excuse to not publish information that could hold their departments to account. “There’s sometimes a reluctance to get data out from the civil service; and whilst we see many examples of people understanding the reasons why data has been put to use, I’d say the general default is still not pro-release”.
Other countries take a different view, however. Singapore, for example, publishes much less data than Britain, but has more of a push on making its data accurate to assist startups and app builders….(More)”

“Smart” Cities and the Urban Digital Revolution

Curated on Posted on by Stefaan Verhulst

Shawn DuBravac at Re/Code: “Smog, sewage and congestion are three of the hallmarks of contemporary urban living. But these downsides to city living are gradually becoming things of the past. City planners are finding new ways to address these inefficiencies, leveraging connected technology to create smarter hubs that work for city dwellers.
Welcome to the era of “smart” cities. Advances in wireless sensor systems, information and communication technology (ICT), and infrastructure allow cities to collect and curate huge amounts of data capable of sustaining and improving urban life thanks to the new and ever-growing web of connected technology: The Internet of Things (IoT).
Last year, Los Angeles became the first city in the world to synchronize its traffic lights — all 4,500 of them — reducing traffic time on major LA corridors by about 12 percent, according to the city’s Department of Transportation. In Singapore, city authorities are testing smart systems for managing parking and waste disposal to adjust to daily and weekly patterns. In New York City, mobile air pollution monitors help city leaders pinpoint those neighborhoods most affected by smog and pollutants, so residents can modify their commuting paths and preferred modes of transportation to avoid exposure to higher levels of pollution.
And cities across the U.S. — including Chicago, Seattle and Washington, D.C. — are hiring chief technology officers to oversee broad implementation of digital systems and technologies. As more and more city functions evolve from analog to digital, it makes sense for municipalities to put the improvement, functionality and security of those systems into one department. These city CTOs will quickly become indispensable cabinet positions….”

Singapore encourages use of private sector datasets

Curated on Posted on by Stefaan Verhulst
Charlene Chin at Future Gov:  “Singapore’s Infocomm Development Authority launched a data-sharing challenge to encourage the use of private sector datasets.

The Data Discovery Challenge, launched last week, aims to promote the combination of private and public datasets to develop products and services that can benefit businesses and the public.
The challenge will use Singapore’s new platform, the Federated Dataset Registry (FDSR), to share public and private sector datasets. According to IDA, many private datasets are residing in siloed servers, or can only be made available through cumbersome processes such as the use of CD-ROMs. The FDSR will enable users to use these private datasets that were previously unconnected.
“Currently, there is no coherent mechanism for users to easily discover private sector datasets made available from data providers across various [industries]”, IDA said.
The Data Discovery Challenge is open from the 11 December to 25 January next year. Participants will have to use datasets from the FDSR and integrate it with any public and private datasets to develop data visualisation tools, mobile or web applications….”

An Open Government Index: From Democracy to Efficiency to Innovation

Curated on Posted on by Stefaan Verhulst

New Report by Lindgren, Tony; Ekenberg, Love; Nouri, Jalal and Hansson, Karin: “Most research in research areas like E-government, E-participation and Open government assume a democratic norm. The concept of Open government, recently promoted by, e.g., The Obama administration and the European Commission is to a large extent based on a general liberal and deliberative ideology emphasizing transparency, participation and collaboration. The concept has also become of interest for states like China and Singapore. In this position paper we outline how to study the concept under different political discourses and suggest an Open government index that can be used to analyze the concept of open government under various settings. (More)”