Open Mobility Foundation

Curated on Posted on by Stefaan Verhulst

Press Release: “The Open Mobility Foundation (OMF) – a global coalition led by cities committed to using well-designed, open-source technology to evolve how cities manage transportation in the modern era – launched today with the mission to promote safety, equity and quality of life. The announcement comes as a response to the growing number of vehicles and emerging mobility options on city streets. A new city-governed non-profit, the OMF brings together academic, commercial, advocacy and municipal stakeholders to help cities develop and deploy new digital mobility tools, and provide the governance needed to efficiently manage them.

“Cities are always working to harness the power of technology for the public good. The Open Mobility Foundation will help us manage emerging transportation infrastructures, and make mobility more accessible and affordable for people in all of our communities,” said Los Angeles Mayor Eric Garcetti, who also serves as Advisory Council Chair of Accelerator for America, which showcased the MDS platform early on.

The OMF convenes a new kind of public-private forum to seed innovative ideas and govern an evolving software platform. Serving as a forum for discussions about pedestrian safety, privacy, equity, open-source governance and other related topics, the OMF has engaged a broad range of city and municipal organizations, private companies and non-profit groups, and experts and advocates to ensure comprehensive engagement and expertise on vital issues….

The OMF governs a platform called “Mobility Data Specification” (MDS) that the Los Angeles Department of Transportation developed to help manage dockless micro-mobility programs (including shared dockless e-scooters). MDS is comprised of a set of Application Programming Interfaces (APIs) that create standard communications between cities and private companies to improve their operations. The APIs allow cities to collect data that can inform real-time traffic management and public policy decisions to enhance safety, equity and quality of life. More than 50 cities across the United States – and dozens across the globe – already use MDS to manage micro-mobility services.

Making this software open and free offers a safe and efficient environment for stakeholders, including municipalities, companies, experts and the public, to solve problems together. And because private companies scale best when cities can offer a consistent playbook for innovation, the OMF aims to nurture those services that provide the highest benefit to the largest number of people, from sustainability to safety outcomes….(More)”

Challenges in using data across government

Curated on Posted on by Stefaan Verhulst

National Audit Office (UK): “Data is crucial to the way government delivers services for citizens, improves its own systems and processes, and makes decisions. Our work has repeatedly highlighted the importance of evidence-based decision-making at all levels of government activity, and the problems that arise when data is inadequate.

Government recognises the value of using data more effectively, and the importance of ensuring security and public trust in how it is used. It plans to produce a new national data strategy in 2020 to position “the UK as a global leader on data, working collaboratively and openly across government”.

To achieve its ambitions government will need to resolve fundamental challenges around how to use and share data safely and appropriately, and how to balance competing demands on public resources in a way that allows for sustained but proportionate investment in data. The future national data strategy provides the government with an opportunity to do this, building on the renewed interest and focus on the use of data within government and beyond.

Content and scope of the report

This report sets out the National Audit Office’s experience of data across government, including initial efforts to start to address the issues. From our past work we have identified three areas where government needs to establish the pre-conditions for success: clear strategy and leadership; a coherent infrastructure for managing data; and broader enablers to safeguard and support the better use of data. In this report we consider:

  • the current data landscape across government (Part One);
  • how government needs a clear plan and leadership to improve its use of data (Part Two);
  • the quality, standards and systems needed to use data effectively (Part Three); and
  • wider conditions and enablers for success (Part Four).

Concluding remarks

Past examples such as Windrush and Carer’s Allowance show how important good‑quality data is, and the consequences if not used well. Without accurate, timely and proportionate data, government will not be able get the best use out of public money or take the next step towards more sophisticated approaches to using data that can reap real rewards.

But despite years of effort and many well-documented failures, government has lacked clear and sustained strategic leadership on data. This has led to departments under-prioritising their own efforts to manage and improve data. There are some early signs that the situation is improving, but unless government uses the data strategy to push a sea change in strategy and leadership, it will not get the right processes, systems and conditions in place to succeed, and this strategy will be yet another missed opportunity….(More)”.

Open Urban Data and the Sustainable Development Goals

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Conference Paper by Christine Meschede and Tobias Siebenlist: “Since the adoption of the United Nations’ Sustainable Development Goals (SDGs) in 2015 – an ambitious agenda to end poverty, combat environmental threats and ensure prosperity for everyone – some effort has been made regarding the adequate measuring of the progress on its targets. As the crucial point is the availability of sufficient, comparable information, open data can play a key role. The coverage of open data, i.e., data that is machine-readable, freely available and reusable for everyone, is assessed by several measurement tools. We propose the use of open governmental data to make the achievement of SDGs easy and transparent to measure. For this purpose, a mapping of the open data categories to the SDGs is presented. Further, we argue that the SDGs need to be tackled in particular at the city level. For analyzing the current applicability of open data for measuring progress on the SDGs, we provide a small-scale case study on German open data portals and the embedded data categories and datasets. The results suggest that further standardization is needed in order to be able to use open data for comparing cities and their progress towards the SDGs….(More)”.

Access to Data in Connected Cars and the Recent Reform of the Motor Vehicle Type Approval Regulation

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Paper by Wolfgang Kerber and Daniel Moeller: “The need for regulatory solutions for access to in-vehicle data and resources of connected cars is one of the big controversial and unsolved policy issues. Last year the EU revised the Motor Vehicle Type Approval Regulation which already entailed a FRAND-like solution for the access to repair and maintenance information (RMI) to protect competition on the automotive aftermarkets. However, the transition to connected cars changes the technological conditions for this regulatory solution significantly. This paper analyzes the reform of the type approval regulation and shows that the regulatory solutions for access to RMI are so far only very insufficiently capable of dealing with the challenges coming along with increased connectivity, e.g. with regard to the new remote diagnostic, repair and maintenance services. Therefore, an important result of the paper is that the transition to connected cars will require a further reform of the rules for the regulated access to RMI (esp. with regard to data access, interoperability, and safety/security issues). However, our analysis also suggests that the basic approach of the current regulated access regime for RMI in the type approval regulation can also be a model for developing general solutions for the currently unsolved problems of access to in-vehicle data and resources in the ecosystem of connected driving….(More)”.

Open Data Retrospective

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Laura Bacon at Luminate:: “Our global philanthropic organisation – previously the Government & Citizen Engagement (GCE) initiative at Omidyar Network, now Luminate – has been active in the open data space for over decade. In that time, we have invested more than $50m in organisations and platforms that are working to advance open data’s potential, including Open Data Institute, IMCO, Open Knowledge, ITS Rio, Sunlight, GovLab, Web Foundation, Open Data Charter, and Open Government Partnership.

Ahead of our transition from GCE to Luminate last year, we wanted to take a step back and assess the field in order to cultivate a richer understanding of the evolution of open data—including its critical developments, drivers of change, and influential actors[1]. This research would help inform our own strategy and provide valuable insight that we can share with the broader open data ecosystem. 

First, what is open data? Open data is data that can be freely used, shared, and built-upon by anyone, anywhere, for any purpose. At its best, open government data can empower citizens, improve governments, create opportunities, and help solve public problems. Have you used a transport app to find out when the next bus will arrive? Or a weather app to look up a forecast? When using a real estate website to buy or rent a home, have you also reviewed its proximity to health, education, and recreational facilities or checked out neighborhood crime rates? If so, your life has been impacted by open data. 

The Open Data Retrospective

We commissioned Dalberg, a global strategic advisory firm, to conduct an Open Data Retrospective to explore: ‘how and why did the open data field evolve globally over the past decade?’ as well as ‘where is the field today?’ With the concurrent release of the report “The State of Open Data” – led by IDRC and Open Data for Development initiative – we thought this would be a great time to make public the report we’d commissioned. 

You can see Dalberg’s open data report here, and its affiliated data here. Please note, this presentation is a modification of the report. Several sections and slides have been removed for brevity and/or confidentiality. Therefore, some details about particular organisations and strategies are not included in this deck.

Evolution and impact

Dalberg’s report covers the trajectory of the open data field and characterised it as: inception (pre-2008), systematisation (2009-2010), expansion (2011-2015), and reevaluation (2016-2018).This characterisation varies by region and sector, but generally captures the evolution of the open data movement….(More)”.

The war to free science

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Brian Resnick and Julia Belluz at Vox: “The 27,500 scientists who work for the University of California generate 10 percent of all the academic research papers published in the United States.

Their university recently put them in a strange position: Sometime this year, these scientists will not be able to directly access much of the world’s published research they’re not involved in.

That’s because in February, the UC system — one of the country’s largest academic institutions, encompassing Berkeley, Los Angeles, Davis, and several other campuses — dropped its nearly $11 million annual subscription to Elsevier, the world’s largest publisher of academic journals.

On the face of it, this seemed like an odd move. Why cut off students and researchers from academic research?

In fact, it was a principled stance that may herald a revolution in the way science is shared around the world.

The University of California decided it doesn’t want scientific knowledge locked behind paywalls, and thinks the cost of academic publishing has gotten out of control.

Elsevier owns around 3,000 academic journals, and its articles account for some 18 percentof all the world’s research output. “They’re a monopolist, and they act like a monopolist,” says Jeffrey MacKie-Mason, head of the campus libraries at UC Berkeley and co-chair of the team that negotiated with the publisher.Elsevier makes huge profits on its journals, generating billions of dollars a year for its parent company RELX .

This is a story about more than subscription fees. It’s about how a private industry has come to dominate the institutions of science, and how librarians, academics, and even pirates are trying to regain control.

The University of California is not the only institution fighting back. “There are thousands of Davids in this story,” says University of California Davis librarian MacKenzie Smith, who, like so many other librarians around the world, has been pushing for more open access to science. “But only a few big Goliaths.”…(More)”.

Data & Policy: A new venue to study and explore policy–data interaction

Curated on Posted on by Stefaan Verhulst

Opening editorial by Stefaan G. Verhulst, Zeynep Engin and Jon Crowcroft: “…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. ….

  • Despite the number of successful prototypes and small-scale initiatives, policy makers’ understanding of data’s potential and its value proposition generally remains limited (Lutes, 2015). There is also limited appreciation of the advances data science has made the last few years. This is a major limiting factor; we cannot expect policy makers to use data if they do not recognize what data and data science can do.
  • The recent (and justifiable) backlash against how certain private companies handle consumer data has had something of a reverse halo effect: There is a growing lack of trust in the way data is collected, analyzed, and used, and this often leads to a certain reluctance (or simply risk-aversion) on the part of officials and others (Engin, 2018).
  • Despite several high-profile open data projects around the world, much (probably the majority) of data that could be helpful in governance remains either privately held or otherwise hidden in silos (Verhulst and Young, 2017b). There remains a shortage not only of data but, more specifically, of high-quality and relevant data.
  • With few exceptions, the technical capacities of officials remain limited, and this has obviously negative ramifications for the potential use of data in governance (Giest, 2017).
  • It’s not just a question of limited technical capacities. There is often a vast conceptual and values gap between the policy and technical communities (Thompson et al., 2015; Uzochukwu et al., 2016); sometimes it seems as if they speak different languages. Compounding this difference in world views is the fact that the two communities rarely interact.
  • Yet, data about the use and evidence of the impact of data remain sparse. The impetus to use more data in policy making is stymied by limited scholarship and a weak evidential basis to show that data can be helpful and how. Without such evidence, data advocates are limited in their ability to make the case for more data initiatives in governance.
  • Data are not only changing the way policy is developed, but they have also reopened the debate around theory- versus data-driven methods in generating scientific knowledge (Lee, 1973; Kitchin, 2014; Chivers, 2018; Dreyfuss, 2017) and thus directly questioning the evidence base to utilization and implementation of data within policy making. A number of associated challenges are being discussed, such as: (i) traceability and reproducibility of research outcomes (due to “black box processing”); (ii) the use of correlation instead of causation as the basis of analysis, biases and uncertainties present in large historical datasets that cause replication and, in some cases, amplification of human cognitive biases and imperfections; and (iii) the incorporation of existing human knowledge and domain expertise into the scientific knowledge generation processes—among many other topics (Castelvecchi, 2016; Miller and Goodchild, 2015; Obermeyer and Emanuel, 2016; Provost and Fawcett, 2013).
  • Finally, we believe that there should be a sound under-pinning a new theory of what we call Policy–Data Interactions. To date, in reaction to the proliferation of data in the commercial world, theories of data management,1 privacy,2 and fairness3 have emerged. From the Human–Computer Interaction world, a manifesto of principles of Human–Data Interaction (Mortier et al., 2014) has found traction, which intends reducing the asymmetry of power present in current design considerations of systems of data about people. However, we need a consistent, symmetric approach to consideration of systems of policy and data, how they interact with one another.

All these challenges are real, and they are sticky. We are under no illusions that they will be overcome easily or quickly….

During the past four conferences, we have hosted an incredibly diverse range of dialogues and examinations by key global thought leaders, opinion leaders, practitioners, and the scientific community (Data for Policy, 2015, 2016, 2017, 2019). What became increasingly obvious was the need for a dedicated venue to deepen and sustain the conversations and deliberations beyond the limitations of an annual conference. This leads us to today and the launch of Data & Policy, which aims to confront and mitigate the barriers to greater use of data in policy making and governance.

Data & Policy is a venue for peer-reviewed research and discussion about the potential for and impact of data science on policy. Our aim is to provide a nuanced and multistranded assessment of the potential and challenges involved in using data for policy and to bridge the “two cultures” of science and humanism—as CP Snow famously described in his lecture on “Two Cultures and the Scientific Revolution” (Snow, 1959). By doing so, we also seek to bridge the two other dichotomies that limit an examination of datafication and is interaction with policy from various angles: the divide between practice and scholarship; and between private and public…

So these are our principles: scholarly, pragmatic, open-minded, interdisciplinary, focused on actionable intelligence, and, most of all, innovative in how we will share insight and pushing at the boundaries of what we already know and what already exists. We are excited to launch Data & Policy with the support of Cambridge University Press and University College London, and we’re looking for partners to help us build it as a resource for the community. If you’re reading this manifesto it means you have at least a passing interest in the subject; we hope you will be part of the conversation….(More)”.

From Theory to Practice : Open Government Data, Accountability, and Service Delivery

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Report by Michael Christopher Jelenic: “Open data and open government data have recently attracted much attention as a means to innovate, add value, and improve outcomes in a variety of sectors, public and private. Although some of the benefits of open data initiatives have been assessed in the past, particularly their economic and financial returns, it is often more difficult to evaluate their social and political impacts. In the public sector, a murky theory of change has emerged that links the use of open government data with greater government accountability as well as improved service delivery in key sectors, including health and education, among others. In the absence of cross-country empirical research on this topic, this paper asks the following: Based on the evidence available, to what extent and for what reasons is the use of open government data associated with higher levels of accountability and improved service delivery in developing countries?

To answer this question, the paper constructs a unique data set that operationalizes open government data, government accountability, service delivery, as well as other intervening and control variables. Relying on data from 25 countries in Sub-Saharan Africa, the paper finds a number of significant associations between open government data, accountability, and service delivery. However, the findings suggest differentiated effects of open government data across the health and education sectors, as well as with respect to service provision and service delivery outcomes. Although this early research has limitations and does not attempt to establish a purely causal relationship between the variables, it provides initial empirical support for claims about the efficacy of open government data for improving accountability and service delivery….(More)”

How to use data for good — 5 priorities and a roadmap

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Stefaan Verhulst at apolitical: “…While the overarching message emerging from these case studies was promising, several barriers were identified that if not addressed systematically could undermine the potential of data science to address critical public needs and limit the opportunity to scale the practice more broadly.

Below we summarise the five priorities that emerged through the workshop for the field moving forward.

1. Become People-Centric

Much of the data currently used for drawing insights involve or are generated by people.

These insights have the potential to impact people’s lives in many positive and negative ways. Yet, the people and the communities represented in this data are largely absent when practitioners design and develop data for social good initiatives.

To ensure data is a force for positive social transformation (i.e., they address real people’s needs and impact lives in a beneficiary way), we need to experiment with new ways to engage people at the design, implementation, and review stage of data initiatives beyond simply asking for their consent.

(Photo credit: Image from the people-led innovation report)

As we explain in our People-Led Innovation methodology, different segments of people can play multiple roles ranging from co-creation to commenting, reviewing and providing additional datasets.

The key is to ensure their needs are front and center, and that data science for social good initiatives seek to address questions related to real problems that matter to society-at-large (a key concern that led The GovLab to instigate 100 Questions Initiative).

2. Establish Data About the Use of Data (for Social Good)

Many data for social good initiatives remain fledgling.

As currently designed, the field often struggles with translating sound data projects into positive change. As a result, many potential stakeholders—private sector and government “owners” of data as well as public beneficiaries—remain unsure about the value of using data for social good, especially against the background of high risks and transactions costs.

The field needs to overcome such limitations if data insights and its benefits are to spread. For that, we need hard evidence about data’s positive impact. Ironically, the field is held back by an absence of good data on the use of data—a lack of reliable empirical evidence that could guide new initiatives.

The field needs to prioritise developing a far more solid evidence base and “business case” to move data for social good from a good idea to reality.

3. Develop End-to-End Data Initiatives

Too often, data for social good focus on the “data-to-knowledge” pipeline without focusing on how to move “knowledge into action.”

As such, the impact remains limited and many efforts never reach an audience that can actually act upon the insights generated. Without becoming more sophisticated in our efforts to provide end-to-end projects and taking “data from knowledge to action,” the positive impact of data will be limited….

4. Invest in Common Trust and Data Steward Mechanisms 

For data for social good initiatives (including data collaboratives) to flourish and scale, there must be substantial trust between all parties involved; and amongst the public-at-large.

Establishing such a platform of trust requires each actor to invest in developing essential trust mechanisms such as data governance structures, contracts, and dispute resolution methods. Today, designing and establishing these mechanisms take tremendous time, energy, and expertise. These high transaction costs result from the lack of common templates and the need to each time design governance structures from scratch…

5. Build Bridges Across Cultures

As C.P. Snow famously described in his lecture on “Two Cultures and the Scientific Revolution,” we must bridge the “two cultures” of science and humanism if we are to solve the world’s problems….

To implement these five priorities we will need experimentation at the operational but also institutional level. This involves the establishment of “data stewards” within organisations that can accelerate data for social good initiative in a responsible manner integrating the five priorities above….(More)”

We should extend EU bank data sharing to all sectors

Curated on Posted on by Stefaan Verhulst

Carlos Torres Vila in the Financial Times: “Data is now driving the global economy — just look at the list of the world’s most valuable companies. They collect and exploit the information that users generate through billions of online interactions taking place every day. 


But companies are hoarding data too, preventing others, including the users to whom the data relates, from accessing and using it. This is true of traditional groups such as banks, telcos and utilities, as well as the large digital enterprises that rely on “proprietary” data. 
Global and national regulators must address this problem by forcing companies to give users an easy way to share their own data, if they so choose. This is the logical consequence of personal data belonging to users. There is also the potential for enormous socio-economic benefits if we can create consent-based free data flows. 
We need data-sharing across companies in all sectors in a real time, standardised way — not at a speed and in a format dictated by the companies that stockpile user data. These new rules should apply to all electronic data generated by users, whether provided directly or observed during their online interactions with any provider, across geographic borders and in any sector. This could include everything from geolocation history and electricity consumption to recent web searches, pension information or even most recently played songs. 

This won’t be easy to achieve in practice, but the good news is that we already have a framework that could be the model for a broader solution. The UK’s Open Banking system provides a tantalising glimpse of what may be possible. In Europe, the regulation known as the Payment Services Directive 2 allows banking customers to share data about their transactions with multiple providers via secure, structured IT interfaces. We are already seeing this unlock new business models and drive competition in digital financial services. But these rules do not go far enough — they only apply to payments history, and that isn’t enough to push forward a data-driven economic revolution across other sectors of the economy. 

We need a global framework with common rules across regions and sectors. This has already happened in financial services: after the 2008 financial crisis, the G20 strengthened global banking standards and created the Financial Stability Board. The rules, while not perfect, have delivered uniformity which has strengthened the system. 

We need a similar global push for common rules on the use of data. While it will be difficult to achieve consensus on data, and undoubtedly more difficult still to implement and enforce it, I believe that now is the time to decide what we want. The involvement of the G20 in setting up global standards will be essential to realising the potential that data has to deliver a better world for all of us. There will be complaints about the cost of implementation. I know first hand how expensive it can be to simultaneously open up and protect sensitive core systems. 

The alternative is siloed data that holds back innovation. There will also be justified concerns that easier data sharing could lead to new user risks. Security must be a non-negotiable principle in designing intercompany interfaces and protecting access to sensitive data. But Open Banking shows that these challenges are resolvable. …(More)”.