Commons Framework Research Articles

Twitter as Knowledge Commons: What Twitter Users Think and Do About Managing Misinformation Issues

ABSTRACTBased on the Governing Knowledge Commons framework, this study examines what users do and think about managing misinformation issues in the Twitter community, and how these are affected by user characteristics. Undergraduates from a public university in the US participated in the study (n = 464) by completing an online survey. Findings shed light on how Twitter community members tackle misinformation issues and inform policies and system designs to support the members' actions and preferences.

ARDaC Common Data Model Facilitates Data Dissemination and Enables Data Commons for Modern Clinical Studies.

Modern clinical studies collect longitudinal and multimodal data about participants, treatments and responses, biospecimens, and molecular and multiomics data. Such rich and complex data requires new common data models (CDM) to support data dissemination and research collaboration. We have developed the ARDaC CDM for the Alcoholic Hepatitis Network (AlcHepNet) Research Data Commons (ARDaC) to support clinical studies and translational research in the national AlcHepNet consortium. The ARDaC CDM bridges the gap between the data models used by the AlcHepNet electronic data capture platform (REDCap) and the Genomic Data Commons (GDC) data model used by the Gen3 data commons framework. It extends the GDC data model for clinical studies; facilitates the harmonization of research data across consortia and programs; and supports the development of the ARDaC. ARDaC CDM is designed as a general and extensible CDM for addressing the needs of modern clinical studies. The ARDaC CDM is available at https://dev.ardac.org/DD.

The planetary commons: A new paradigm for safeguarding Earth-regulating systems in the Anthropocene

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework—the planetary commons—which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical systems that regulate the resilience and state, and therefore livability, on Earth. The new planetary commons should articulate and create comprehensive stewardship obligations through Earth system governance aimed at restoring and strengthening planetary resilience and justice.

Markets and knowledge commons: Is there a difference between private and community governance of markets?

AbstractIt is well-established that market governance can be provided by both public (state) and private organizations. However, the concept of private governance has been used, this article contends, to refer to two distinct forms of non-state governance: private governance and community governance. We distinguish between these two forms, arguing that private governance should be understood as the provision of market governance by (external) private parties, while community governance refers to a process where a group, a community, or society has the autonomy to govern its own affairs without interference from external authorities. The former internalizes the externalities associated with governance, while the latter comes about mainly as an unintended externality of social interaction in markets. To further illuminate the differences, and the relative strengths of these types of non-state governance, we distinguish among three elements of market governance: (1) the formation and interpretation of rules, (2) the administration of rules of ownership and exchange, and (3) the enforcement of rules. We argue that community governance is of great relevance for the formation and interpretation of the rules of ownership and exchange, which is consequently very hard to outsource to external parties, private or public. Community governance also plays a frequently overlooked role in administration and enforcement through the process of co-production. Rule formation and interpretation are theorized as the epistemic components of market governance, which can be analyzed within the Governing Knowledge Commons framework.

Slow-governance in smart cities: An empirical study of smart intersection implementation in four US college towns

This empirical study of governance and ethics regarding the adoption of smart intersection in four US college towns, structured by the Governing Knowledge Commons (GKC) framework, calls for deliberative, slow-governance of public data to respect human rights and align with community norms.

Governance and human rights implications of ASEAN's Smart Cities Network: a knowledge commons analysis

AbstractLaunched in April 2018, the Association of Southeast Asian Nations' Smart Cities Network (ASCN) initiative raises important issues regarding the tensions between achieving smart city objectives on the one hand and protection of human rights on the other. The aim of this paper is to explore these tensions using a Knowledge Commons Framework analysis. I first analyse the three key pillars of the ASCN pilot city knowledge commons – knowledge resources, community attributes and governance ‘rules in use’ – using human rights criteria. I the apply the lessons of this analysis to two fundamental aspects of human experience in smart city contexts – mobility through transport systems and access to essential services through energy supply.

Communication for food commons: a comparative analysis of community supported agriculture in Portugal

This study departs from a commons framework of analysis to compare the internal communication practices of seven csas from Portugal. By looking at governance, economy, knowledge, technology and eco-social justice, our findings reveal there is no food commoning without communication. Based on action-research and militant ethnography methods, the study combines a focus group, visual methods and interviews, and contributes with an original approach to communication studies from a commons epistemology.

Too Much of a Good Thing? A Governing Knowledge Commons Review of Abundance in Context.

The economics of abundance, along with the sociology of abundance, the law of abundance, and so forth, should be re-framed, linked, and situated in a common context for empirical rather than conceptual research. Abundance may seem to be a new, big thing, between anxiety over information overload, Big Data, and related technological disruptions. But scholars know that abundance is an ancient phenomenon, which only seemed to disappear as twentieth century social science focused on scarcity instead. Restoring the study of abundance, and figuring out how to solve the problems that abundance might create, means shedding disciplinary blinders and going back to basics. How does abundance, in various forms, create or alleviate social problems? We explain and illustrate how the Governing Knowledge Commons (GKC) framework provides a useful research tool to generate and test hypotheses about abundance in various economic, social, cultural, and legal settings.

Blockchain Networks as Knowledge Commons

Researchers interested in blockchains are increasingly attuned to questions of governance, including how blockchains relate to government, the ways blockchains are governed, and ways blockchains can improve prospects for successful self-governance. Our paper joins this research by exploring the implications of the Governing Knowledge Commons (GKC) framework to analyze governance of blockchains. Our novel contributions are making the case that blockchain networks represent knowledge commons governance, in the sense that they rely on collectively-managed technologies to pool and manage distributed information, illustrating the usefulness and novelty of the GCK methodology with an empirical case study of the evolution of Bitcoin, and laying the foundation for a research program using the GKC approach.

Information governance for sustainable development: Exploring social dilemmas in data provision for international reporting on Land Degradation Neutrality

In 2015, the United Nations (UN) adopted the Sustainable Development Goals (SDGs). Sub-goal 15.3 aims to achieve "Land Degradation Neutrality" (LDN) by 2030 through the efforts of UN member states. Countries committed to LDN are encouraged to report on progress to the UN by tracking three globally recognized indicators: land cover, land productivity, and soil organic carbon stocks. This requires the adoption of a methodology for accurately assessing land degradation and the availability of mechanisms for collecting and reporting the data. In Kyrgyzstan, the first LDN report identified a serious gap in national carbon stock data and a lack of standard procedures for monitoring and reporting on all three LDN indicators. Recent efforts to develop scientifically sound methods for assessing soil organic carbon stocks and calculating the other two indicators based on available national datasets could help address these deficiencies. However, to be effective, methodological advances need to be embedded in a suitable institutional architecture. Based on semi-structured interviews with local experts, this study shows how the institutional context within which information users and producers interact affects the provision of environmental data required by international agreements. Drawing on the knowledge commons framework, this paper identifies and describes three social dilemmas at the root of tensions in information governance that affect LDN reporting in the Kyrgyz context. The study also identifies opportunities for learning and improvement and highlights key issues that are relevant beyond the LDN context and could contribute to enhancing monitoring and reporting on environmental dimensions of other SDGs.

Dismantling AI capitalism: the commons as an alternative to the power concentration of Big Tech.

This article discusses the political economy of AI capitalism. It considers AI as a General Purpose Technology (GPT) and argues we need to investigate the power concentration of Big Tech. AI capitalism is characterised by the commodification of data, data extraction and a concentration in hiring of AI talent and compute capacity. This is behind Big Tech’s unstoppable drive for growth, which leads to monopolisation and enclosure under the winner takes all principle. If we consider AI as a GPT—technologies that alter society’s economic and social structures—we need to come up with alternatives in terms of ownership and governance. The commons is proposed as an alternative for thinking about how to organise AI development and how to distribute the value that can be derived from it. Using the commons framework is also a way of giving society a more prominent role in the debate about what we expect from AI and how we should approach it.

NCI Imaging Data Commons.

The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of deidentified imaging data and to support integrated analyses with nonimaging data. We achieve this goal by colocating versatile imaging collections with cloud-based computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. SIGNIFICANCE: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud.

BloodPAC Data Commons for Liquid Biopsy Data.

PURPOSEThe Blood Profiling Atlas in Cancer (BloodPAC) Data Commons (BPDC) is being developed and is operated by the public-private BloodPAC Consortium to support the liquid biopsy community. It is an interoperable data commons with the ultimate aim of serving as a recognized source of valid scientific evidence for liquid biopsy assays for industry, academia, and standards and regulatory stakeholders.METHODSThe BPDC is implemented using the open source Gen3 data commons platform (https://gen3.org). In particular, the BPDC Data Exploration Portal, BPDC Data Submission Portal, the BPDC Workspace Hub, and the BloodPAC application programming interface (API) were all automatically generated from the BloodPAC Data Model using the Gen3 data commons platform. BPDC uses Gen3's implementation of the data commons framework services so that it can interoperate through secure, compliant APIs with other data commons using data commons framework service, such as National Cancer Institute's Cancer Research Data Commons.RESULTSThe BPDC contains 57 studies and projects spanning more than 4,100 cases. This amounts to 5,700 aliquots (blood plasma, serum, or a contrived sample) that have been subjected to a liquid biopsy assay, quantified, and then contributed by members of the BloodPAC Consortium. In all, there are more than 31,000 files in the commons as of December 2020. We describe the BPDC, the data it manages, the process that the BloodPAC Consortium used to develop it, and some of the applications that have been developed using its API.CONCLUSIONThe BPDC has been the data platform used by BloodPAC during the past 4 years to manage the data for the consortium and to provide workspaces for its working groups.

Norm conflicts as governance challenges for Seed Commons: Comparing cases from Germany and the Philippines

A Seed Commons approach can help to highlight the common struggle of diverse seed initiatives in the Global North and South in light of the dominant pathway of enclosure and commodification of seeds that threatens food sovereignty and cultivated plant-genetic diversity. In this paper, the Seed Commons framework is applied to show how the conflicting norms and rules of the international regime complex surrounding seeds shape the scope of action for Seed Commons in Germany and the Philippines. The analysis shows that the patent and variety protection regimes have strongly influenced the design of national seed marketing and threaten to outlaw practices of Seed Commons. Despite limited practical impact for Seed Commons initiatives (so far), the norms of the Nagoya Protocol and the Seed Treaty have contributed to exceptions in national seed marketing law that provide essential scope of action for Seed Commons initiatives in Europe and the Philippines.

Sharing Patient-Controlled Real-World Data Through the Application of the Theory of Commons: Action Research Case Study

BackgroundTechnological advances have radically changed the opportunities for individuals with chronic conditions to practice self-care and to coproduce health care and research. Digital technologies enable patients to perform tasks traditionally carried out by health care professionals in a more convenient way, at lower costs, and without compromising quality. Patients may also share real-world data with other stakeholders to promote individual and population health. However, there is a need for legal frameworks that enable patient privacy and control in such sharing of real-world data. We believe that this need could be met by the conceptualization of patient-controlled real-world data as knowledge commons, which is a resource shared by a group of people.ObjectiveThis study aimed to propose a conceptual model that describes how patient-controlled real-world data can be shared effectively in chronic care management, in a way that supports individual and population health, while respecting personal data privacy and control.MethodsAn action research approach was used to develop a solution to enable patients, in a self-determined way, to share patient-controlled data to other settings. We chose the context of cystic fibrosis (CF) care in Sweden, where coproduction between patients, their families, and health care professionals is critical in the introduction of new drugs. The first author, who is a lawyer and parent of children with CF, was a driver in the change process. All coauthors collaborated in the analysis. We collected primary and secondary data reflecting changes during the time period from 2012 to 2020, and performed a qualitative content analysis guided by the knowledge commons framework.ResultsThrough a series of changes, a national system for enabling patients to share patient-controlled real-world data to different stakeholders in CF care was implemented. The case analysis resulted in a conceptual model consisting of the following three knowledge commons arenas that contributed to patient-controlled real-world data collection, use, and sharing: (1) patient world arena involving the private sphere of patients and families; (2) clinical microsystem arena involving the professional sphere at frontline health care clinics; and (3) round table arena involving multiple stakeholders from different settings. Based on the specification of property rights, as presented in our model, the patient can keep control over personal health information and may grant use rights to other stakeholders.ConclusionsHealth information exchanges for sharing patient-controlled real-world data are pivotal to enable patients, health care professionals, health care funders, researchers, authorities, and the industry to coproduce high-quality care and to introduce and follow-up novel health technologies. Our model proposes how technical and legal structures that protect the integrity and self-determination of patients can be implemented, which may be applicable in other chronic care settings as well.

Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo

The knowledge commons research framework is applied to a case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis via the Internet. In the second place Galaxy Zoo is a highly successful example of peer production, sometimes known colloquially as crowdsourcing, by which data are gathered, supplied, and/or analyzed by very large numbers of anonymous and pseudonymous contributors to an enterprise that is centrally coordinated or managed. In the third place Galaxy Zoo is a highly visible example of data-intensive science, sometimes referred to as e-science or Big Data science, by which scientific researchers develop methods to grapple with the massive volumes of digital data now available to them via modern sensing and imaging technologies. This chapter synthesizes these three perspectives on Galaxy Zoo via the knowledge commons framework.

Resource allocation at an income‐sharing community: An application of Elinor Ostrom's commons framework

AbstractElinor Ostrom's framework for commons management is used here to analyse ethnographic material from long‐term fieldwork in an income‐sharing community in the United States. By requiring participants to pool labour and share resources for survival and well‐being, income‐sharing communities align with Ostrom's allocation design for common‐pool resources. These communities can figure as a node within the hybrid and polycentric networks designated by Ostrom for equitable and effective commons management, which requires both effective institutional arrangements and shared social capital among system participants. While a case is made for analysing resource‐sharing practices at these communities with Elinor Ostrom's framework, shortcomings and possible future directions are indicated.

Abstract IA24: A modern data commons approach to advance population science

Abstract Since 2014, NCI has been building data science platforms to integrate genetic information about tumors with data on how patients respond to therapy. This work advances the 2011 Institute of Medicine recommendation to build a unified system to collect, integrate, and share cancer data from the widest possible set of research studies. NCI is working to fulfill this recommendation by establishing an NCI Cancer Research Data Commons (CRDC), virtual, expandable informatics infrastructure and data repositories, which are designed to support the work of the NCI intramural and extramural cancer research communities. The CRDC is a crucial component of a broader National Cancer Data Ecosystem that spans discovery research, patient participation, and population surveillance. The development of such an ecosystem was a key recommendation of the Cancer Moonshot Blue Ribbon Panel. NCI has been developing the Cancer Research Data Commons based on the understanding that big data emerging from research programs, precision medicine trials, and surveillance can be used to develop and inform models that predict how patients will response to treatment. Numerous NCI-funded programs will provide key data for this ecosystem, including a variety of discovery programs, clinical trials, cohort studies, and NCI’s Surveillance, Epidemiology, and End Results program (SEER), which is the most comprehensive source of population-based information in the country that includes stage of cancer, detailed characterization of the cancer including important biomarkers at the time of diagnosis, and performs active follow-up to determine patient survival data. The CRDC is designed to be as flexible as possible so that many types and sources of data can be accessed in a unified, interoperable manner. It is this data interoperability that facilitates novel insights into cancer biology and treatment. During the past several years, NCI has been developing key building blocks that comprise the CRDC. These building blocks include (i) Data Commons Nodes, which are repositories that house harmonized data from multiple programs; (ii) Cloud Resources, which provide workspaces, analysis capabilities, and access to elastic computing resources in commercial cloud environments; (iii) a Data Commons Framework (DCF), which is a set of modular, reusable services that maximize interoperability across cancer datatypes and repositories, increase sustainability, and reduce future resource cost; and (iv) semantics services to support data models, vocabularies, ontologies, data submission, and cross-domain queries. The modular design of the CRDC means that new services and components can be added flexibly, which allows for new data sources and new technologies to become integrated as they become available. The NCI Cancer Research Data Commons will serve as a platform for understanding fundamental cancer biology questions, including cancer initiation, progression, and recurrence, in ways that support new prevention, treatment, and surveillance strategies. Citation Format: Anthony Kerlavage. A modern data commons approach to advance population science [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA24.

Institutional Determinants of Budgetary Expenditures. A BMA-Based Re-Evaluation of Contemporary Theories for OECD Countries

The article tackles the problem of the most important institutional determinants of public expenditures. Within the traditions of public choice and institutional economics, it tests several theories ranging from the fiscal commons framework, Political Business/Budget Cycle (PBC) and path dependence to veto players theory. Its novelty compared to previous research stems from an attempt to test several theories simultaneously, dealing with model uncertainty by using sensitivity analysis within the Bayesian Model Averaging framework with a vast prior structure in terms of model, g and multicollinearity dilution priors. The results confirm several hypotheses tested in the area of fiscal management across the recent decades within the group of developed economies, giving especially strong support to the tragedy of the fiscal commons and path dependence concepts, while only partial support to veto players theory. In contrast, explanations based on political budget cycle (PBC) theory are dismissed. Among other interesting findings reported in the study, Scandinavian countries turn out to be the most fiscally responsible when other institutional factors are taken into account. Similarly, contrary to other recent research into the issue of EU fiscal institutional framework, Euro area countries are characterized by limited public expenditures.

Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.

Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear. The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses. Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles. Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework. The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science."