Harnessing Data Innovation for Migration Policy: A Handbook for Practitioners

Curated on Posted on by Stefaan Verhulst

Report by IOM: “The Practitioners’ Handbook provides first-hand insights into why and how non-traditional data sources can contribute to better understanding migration-related phenomena. The Handbook aims to (a) bridge the practical and technical aspects of using data innovations in migration statistics, (a) demonstrate the added value of using new data sources and innovative methodologies to analyse key migration topics that may be hard to fully grasp using traditional data sources, and (c) identify good practices in addressing issues of data access and collaboration with multiple stakeholders (including the private sector), ethical standards, and security and data protection issues…(More)” See also Big Data for Migration Alliance.

Whose data commons? Whose city?

Curated on Posted on by Stefaan Verhulst

Blog by Gijs van Maanen and Anna Artyushina: “In 2020, the notion of data commons became a staple of the new European Data Governance Strategy, which envisions data cooperatives as key players of the European Union’s (EU) emerging digital market. In this new legal landscape, public institutions, businesses, and citizens are expected to share their data with the licensed data-governance entities that will oversee its responsible reuse. In 2022, the Open Future Foundation released several white papers where the NGO (non-govovernmental organisation) detailed a vision for the publicly governed and funded EU level data commons. Some academic researchers see data commons as a way to break the data silos maintained and exploited by Big Tech and, potentially, dismantle surveillance capitalism.

In this blog post, we discuss data commons as a concept and practice. Our argument here is that, for data commons to become a (partial) solution to the issues caused by data monopolies, they need to be politicised. As smart city scholar Shannon Mattern pointedly argues, the city is not a computer. This means that digitization and datafication of our cities involves making choices about what is worth digitising and whose interests are prioritised. These choices and their implications must be foregrounded when we discuss data commons or any emerging forms of data governance. It is important to ask whose data is made common and, subsequently, whose city we will end up living in. ..(More)”

Data Cooperatives as Catalysts for Collaboration, Data Sharing, and the (Trans)Formation of the Digital Commons

Curated on Posted on by Stefaan Verhulst

Paper by Michael Max Bühler et al: “Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship (SDG9), new skills, and jobs (SDG8), especially in small communities (SDG11) and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being (SDG3), and protect digital rights, we propose data cooperatives [1,2] as a vehicle for secure, trusted, and sovereign data exchange [3,4]. In post-pandemic times, community/SME-led cooperatives can play a vital role by ensuring that supply chains to support digital commons are uninterrupted, resilient, and decentralized [5]. Digital commons and data sovereignty provide communities with affordable and easy access to information and the ability to collectively negotiate data-related decisions. Moreover, cooperative commons (a) provide access to the infrastructure that underpins the modern economy, (b) preserve property rights, and (c) ensure that privatization and monopolization do not further erode self-determination, especially in a world increasingly mediated by AI. Thus, governance plays a significant role in accelerating communities’/SMEs’ digital transformation and addressing their challenges. Cooperatives thrive on digital governance and standards such as open trusted Application Programming Interfaces (APIs) that increase the efficiency, technological capabilities, and capacities of participants and, most importantly, integrate, enable, and accelerate the digital transformation of SMEs in the overall process. This policy paper presents and discusses several transformative use cases for cooperative data governance. The use cases demonstrate how platform/data-cooperatives, and their novel value creation can be leveraged to take digital commons and value chains to a new level of collaboration while addressing the most pressing community issues. The proposed framework for a digital federated and sovereign reference architecture will create a blueprint for sustainable development both in the Global South and North…(More)”

Responding to the coronavirus disease-2019 pandemic with innovative data use: The role of data challenges

Curated on Posted on by Stefaan Verhulst

Paper by Jamie Danemayer, Andrew Young, Siobhan Green, Lydia Ezenwa and Michael Klein: “Innovative, responsible data use is a critical need in the global response to the coronavirus disease-2019 (COVID-19) pandemic. Yet potentially impactful data are often unavailable to those who could utilize it, particularly in data-poor settings, posing a serious barrier to effective pandemic mitigation. Data challenges, a public call-to-action for innovative data use projects, can identify and address these specific barriers. To understand gaps and progress relevant to effective data use in this context, this study thematically analyses three sets of qualitative data focused on/based in low/middle-income countries: (a) a survey of innovators responding to a data challenge, (b) a survey of organizers of data challenges, and (c) a focus group discussion with professionals using COVID-19 data for evidence-based decision-making. Data quality and accessibility and human resources/institutional capacity were frequently reported limitations to effective data use among innovators. New fit-for-purpose tools and the expansion of partnerships were the most frequently noted areas of progress. Discussion participants identified building capacity for external/national actors to understand the needs of local communities can address a lack of partnerships while de-siloing information. A synthesis of themes demonstrated that gaps, progress, and needs commonly identified by these groups are relevant beyond COVID-19, highlighting the importance of a healthy data ecosystem to address emerging threats. This is supported by data holders prioritizing the availability and accessibility of their data without causing harm; funders and policymakers committed to integrating innovations with existing physical, data, and policy infrastructure; and innovators designing sustainable, multi-use solutions based on principles of good data governance…(More)”.

Seize the Future by Harnessing the Power of Data

Curated on Posted on by Stefaan Verhulst

Essay by Kriss Deiglmeier: “…Data is a form of power. And the sad reality is that power is being held increasingly by the commercial sector and not by organizations seeking to create a more just, sustainable, and prosperous world. A year into my tenure as the chief global impact officer at Splunk, I became consumed with the new era driven by data. Specifically, I was concerned with the emerging data divide, which I defined as “the disparity between the expanding use of data to create commercial value, and the comparatively weak use of data to solve social and environmental challenges.”…

To effectively address the emerging data future, the social impact sector must build an entire impact data ecosystem for this moment in time—and the next moment in time. The way to do that is by investing in those areas where we currently lag the commercial sector. Consider the following gaps:

  • Nonprofits are ill-equipped with the financial and technical resources they need to make full use of data, often due to underfunding.
  • The sector’s technical and data talent is a desert compared to the commercial sector.
  • While the sector is rich with output and service-delivery data, that data is locked away or is unusable in its current form.
  • The sector lacks living data platforms (collaboratives and data refineries) that can make use of sector-wide data in a way that helps improve service delivery, maximize impact, and create radical innovation.

The harsh realities of the sector’s disparate data skills, infrastructure, and competencies show the dire current state. For the impact sector to transition to a place of power, it must jump without hesitation into the arena of the Data Age—and invest time, talent, and money in filling in these gaps.

Regardless of our lagging position, the social sector has both an incredible opportunity and a unique capacity to drive the power of data into the emerging and unimaginable. The good news is that there’s pivotal work already happening in the sector that is making it easier to build the kind of impact data ecosystem needed to join the Data Age. The framing and terms used to describe this work are many—data for good, data science for impact, open data, public interest technology, data lakes, ethical data, and artificial intelligence ethics.

These individual pieces, while important, are not enough. To fully exploit the power of data for a more just, sustainable, and prosperous world, we need to be bold enough to build the full ecosystem and not be satisfied with piecemeal work. To do that we should begin by looking at the assets that we have and build on those.

People. There are dedicated leaders in the field of social innovation who are committed to using data for impact and who have been doing that for many years. We need to support them by investing in their work at scale. The list of people leading the way is constantly growing, but to name a few: Stefaan G. Verhulst, Joy Buolamwini, Jim Fruchterman, Katara McCarty, Geoff Mulgan, Rediet Abebe, Jason Saul, and Jake Porway….(More)”.

Could a Global “Wicked Problems Agency” Incentivize Data Sharing?

Curated on Posted on by Stefaan Verhulst

Paper by Susan Ariel Aaronson: “Global data sharing could help solve “wicked” problems (problems such as climate change, terrorism and global poverty that no one knows how to solve without creating further problems). There is no one or best way to address wicked problems because they have many different causes and manifest in different contexts. By mixing vast troves of data, policy makers and researchers may find new insights and strategies to address these complex problems. National and international government agencies and large corporations generally control the use of such data, and the world has made little progress in encouraging cross-sectoral and international data sharing. This paper proposes a new international cloud-based organization, the “Wicked Problems Agency,” to catalyze both data sharing and data analysis in the interest of mitigating wicked problems. This organization would work to prod societal entities — firms, individuals, civil society groups and governments — to share and analyze various types of data. The Wicked Problems Agency could provide a practical example of how data sharing can yield both economic and public good benefits…(More)”.

An agenda for advancing trusted data collaboration in cities

Curated on Posted on by Stefaan Verhulst

Report by Hannah Chafetz, Sampriti Saxena, Adrienne Schmoeker, Stefaan G. Verhulst, & Andrew J. Zahuranec: “… Joined by experts across several domains including smart cities, the law, and data ecosystem, this effort was focused on developing solutions that could improve the design of Data Sharing Agreements…we assessed what is needed to implement each aspect of our Contractual Wheel of Data Collaboration–a tool developed as a part of the Contracts for Data Collaborations initiative that seeks to capture the elements involved in data collaborations and Data Sharing Agreements.

In what follows, we provide key suggestions from this Action Lab…

  1. The Elements of Principled Negotiations: Those seeking to develop a Data Sharing Agreement often struggle to work with collaborators or agree to common ends. There is a need for a common resource that Data Stewards can use to initiate a principled negotiation process. To address this need, we would identify the principles to inform negotiations and the elements that could help achieve those principles. For example, participants voiced a need for fairness, transparency, and reciprocity principles. These principles could be supported by having a shared language or outlining the minimum legal documents required for each party. The final product would be a checklist or visualization of principles and their associated elements.
  2. Data Responsibility Principles by Design: …
  3. Readiness Matrix: …
  4. A Decision Provenance Approach for Data Collaboration: ..
  5. The Contractual Wheel of Data Collaboration 2.0…
  6. A Repository of Legal Drafting Technologies:…(More)”.

To harness telecom data for good, there are six challenges to overcome

Curated on Posted on by Stefaan Verhulst

Blog by Anat Lewin and Sveta Milusheva: “The global use of mobile phones generates a vast amount of data. What good can be done with these data? During the COVID-19 pandemic, we saw that aggregated data from mobile phones can tell us where groups of humans are going, how many of them are there, and how they are behaving as a cluster. When used effectively and responsibly, mobile phone data can be immensely helpful for development work and emergency response — particularly in resource-constrained countries.  For example, an African country that had, in recent years, experienced a cholera outbreak was ahead of the game. Since the legal and practical agreements were already in place to safely share aggregated mobile data, accessing newer information to support epidemiological modeling for COVID-19 was a straightforward exercise. The resulting datasets were used to produce insightful analyses that could better inform health, lockdown, and preventive policy measures in the country.

To better understand such challenges and opportunities, we led an effort to access and use anonymized, aggregated mobile phone data across 41 countries. During this process, we identified several recurring roadblocks and replicable successes, which we summarized in a paper along with our lessons learned. …(More)”.

Data Collaborative Case Study: NYC Recovery Data Partnership

Curated on Posted on by Stefaan Verhulst

Report by the Open Data Policy Lab (The GovLab): “In July 2020, following severe economic and social losses due to the COVID-19 pandemic, the administration of New York City Mayor Bill de Blasio announced the NYC Recovery Data Partnership. This data collaborative asked private and civic organizations with assets relevant to New York City to provide their data to the city. Senior city leaders from the First Deputy Mayor’s Office, the Mayor’s Office of Operations, Mayor’s Office of Information Privacy and Mayor’s Office of Data Analytics formed an internal coalition which served as trusted intermediaries, assessing agency requests from city agencies to use the data provided and allocating access accordingly. The data informed internal research conducted by various city agencies, including New York City Emergency Management’s Recovery Team and the NYC…(More)”Department of City Planning. The experience reveals the ability of crises to spur innovation, the value of responsiveness from both data users and data suppliers, and the importance of technical capacity, and the value of a network of peers. In terms of challenges, the experience also exposes the limitations of data, the challenges of compiling complex datasets, and the role of resource constraints.

Ten (not so) simple rules for clinical trial data-sharing

Curated on Posted on by Stefaan Verhulst

Paper by Claude Pellen et al: “Clinical trial data-sharing is seen as an imperative for research integrity and is becoming increasingly encouraged or even required by funders, journals, and other stakeholders. However, early experiences with data-sharing have been disappointing because they are not always conducted properly. Health data is indeed sensitive and not always easy to share in a responsible way. We propose 10 rules for researchers wishing to share their data. These rules cover the majority of elements to be considered in order to start the commendable process of clinical trial data-sharing:

  • Rule 1: Abide by local legal and regulatory data protection requirements
  • Rule 2: Anticipate the possibility of clinical trial data-sharing before obtaining funding
  • Rule 3: Declare your intent to share data in the registration step
  • Rule 4: Involve research participants
  • Rule 5: Determine the method of data access
  • Rule 6: Remember there are several other elements to share
  • Rule 7: Do not proceed alone
  • Rule 8: Deploy optimal data management to ensure that the data shared is useful
  • Rule 9: Minimize risks
  • Rule 10: Strive for excellence…(More)”