Policy options to facilitate cancer genomic variant data sharing: outcomes of a modified policy Delphi.

Sharing cancer gene variant and relevant clinical data could accelerate progress in cancer genomics. However, data sharing is currently impeded by issues related to financial sustainability, equity, incentives, privacy and security, and data quality. Evidence-based policy options to facilitate data sharing in these domains, and ultimately improve interpretation of cancer-associated genomic variants, are therefore needed. We conducted a modified policy Delphi with expert stakeholders that involved generating, evaluating, and ranking potential policy options to address these issues, with a focus on the US context. We found policy options in the financial sustainability domain were highly ranked, particularly stable funding for trusted entities. However, some Delphi panelists noted that the culture of public research funding has favored short-term grants. Panelists favored policy options focused on action by funders, which had the highest overall total scores that combined effectiveness and feasibility ratings and priority ranking within domains. Panelists also endorsed some policy options connected to actors such as journals, but they were more skeptical of policy options connected to legislative actors and data resources. These findings are critical inputs for policy makers as they consider policies to enable sharing of cancer gene variant data to improve health.

N-of-1 Analytics Makerspace: A Prototype for Cystic Fibrosis Self-Care and Co-Care.

We have designed a prototype N-of-1 analytics makerspace, which is a collaborative work environment that provides a space for different stakeholders in healthcare to learn new skills and work together on projects that can improve individual patient care and the effectiveness of healthcare systems. Our prototype was designed to study the use of antibiotics in self-management for children with cystic fibrosis in Sweden but is intended to be disease agnostic and potentially include other complex medical conditions in the future.

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.

The gene regulation knowledge commons: the action area of GREEKC.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC.

Documenting and protecting traditional knowledge in the era of open science: Insights from two Spanish initiatives.

ETHNOPHARMACOLOGICAL RELEVANCE: The documentation and protection of traditional knowledge face new challenges in the era of open science. Focusing on medicinal and food uses, we discuss two innovative initiatives in Spain to document, protect and return to the society traditional knowledge. MATERIALS AND METHODS: The Spanish Inventory of Traditional Knowledge related to Biodiversity has compiled and published information on the traditional use and management of flora, fauna, fungi, geodiversity, and ecosystems. CONECT-e (www.conecte.es) is an online platform where citizens can document knowledge and uses of wild and domesticated species. We describe the extent of these initiatives in terms of participation and accomplishment, and discuss their complementarities and challenges. RESULTS: The initiatives described have fostered the establishment of a common standard for organizing traditional knowledge in databases that facilitate knowledge documentation: 131,066 uses and 152,246 local names have been documented so far. Using open data and copyleft licenses, these initiatives also contribute to the maintenance of traditional knowledge in the commons domain, guaranteeing the free exchange and reproduction of knowledge. However, the extensive focus of these initiatives on data sharing does not necessarily guarantee knowledge holders' data sovereignty. CONCLUSION: To protect TEK in a context of open science more efforts should be done to operationalize traditional knowledge holders' rights to data sovereignty.

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

BACKGROUND: Technological 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. OBJECTIVE: This 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. METHODS: An 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. RESULTS: Through 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. CONCLUSIONS: Health 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.

Responsible innovation in synthetic biology in response to COVID-19: the role of data positionality.

Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods-goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally preferred goals. From both an ethical and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality.

Leveraging Research Failures to Accelerate Drug Discovery and Development.

BACKGROUND: Research failures are one of the most significant costs associated with the estimated USD$2.6 billion price tag and 12-year time frame to bring a drug from discovery to market. The European Commission estimates that USD$20 billion are spent every year to develop innovations that have already developed elsewhere, highlighting the exorbitant cost of duplication. The competitive nature of the pharmaceutical industry is such that the voluntary sharing of information is not particularly forthcoming despite the highly publicized advantages of open science, open access, and open innovation. However, sharing research failures may be perceived as less competitively threatening because it is considered 'useless' to the party owning it, but highly valuable to the competition. METHOD: A combination of existing legal tools and technology, such as trade secret protection, blockchain, and knowledge commons, may provide the necessary legal basis for a platform ecosystem that can incentivize and capture the value of sharing intellectual contributions (such as research failures), while protecting innovators against free-riding and unauthorized appropriation by third-parties. RESULT: Not all intellectual efforts that contribute to the creation innovations can be protected by traditional forms of IP. If proprietary information necessary to create innovations cannot be adequately protected, innovators and researchers are likely to safeguard their interests at the expense of sharing. CONCLUSION: A legally supported framework that proactively recognizes intellectual contributions by way of research failures, which can subsequently be translated into a revenue-sharing model, may lead to more openness, value creation, and overall acceleration of drug discovery and development.

Decentralized but Globally Coordinated Biodiversity Data.

Centralized biodiversity data aggregation is too often failing societal needs due to pervasive and systemic data quality deficiencies. We argue for a novel approach that embodies the spirit of the Web ("small pieces loosely joined") through the decentralized coordination of data across scientific languages and communities. The upfront cost of decentralization can be offset by the long-term benefit of achieving sustained expert engagement, higher-quality data products, and ultimately more societal impact for biodiversity data. Our decentralized approach encourages the emergence and evolution of multiple self-identifying communities of practice that are regionally, taxonomically, or institutionally localized. Each community is empowered to control the social and informational design and versioning of their local data infrastructures and signals. With no single aggregator to exert centralized control over biodiversity data, decentralization generates loosely connected networks of mid-level aggregators. Global coordination is nevertheless feasible through automatable data sharing agreements that enable efficient propagation and translation of biodiversity data across communities. The decentralized model also poses novel integration challenges, among which the explicit and continuous articulation of conflicting systematic classifications and phylogenies remain the most challenging. We discuss the development of available solutions, challenges, and outline next steps: the global effort of coordination should focus on developing shared languages for data signal translation, as opposed to homogenizing the data signal itself.

Sharing Data to Build a Medical Information Commons: From Bermuda to the Global Alliance.

The Human Genome Project modeled its open science ethos on nematode biology, most famously through daily release of DNA sequence data based on the 1996 Bermuda Principles. That open science philosophy persists, but daily, unfettered release of data has had to adapt to constraints occasioned by the use of data from individual people, broader use of data not only by scientists but also by clinicians and individuals, the global reach of genomic applications and diverse national privacy and research ethics laws, and the rising prominence of a diverse commercial genomics sector. The Global Alliance for Genomics and Health was established to enable the data sharing that is essential for making meaning of genomic variation. Data-sharing policies and practices will continue to evolve as researchers, health professionals, and individuals strive to construct a global medical and scientific information commons.

ClinGen Pathogenicity Calculator: a configurable system for assessing pathogenicity of genetic variants.

BACKGROUND: The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published standards and guidelines for the interpretation of sequence variants. However, manual application of the guidelines is tedious and prone to human error. Web-based tools and software systems may not only address this problem but also document reasoning and supporting evidence, thus enabling transparency of evidence-based reasoning and resolution of discordant interpretations. RESULTS: In this report, we describe the design, implementation, and initial testing of the Clinical Genome Resource (ClinGen) Pathogenicity Calculator, a configurable system and web service for the assessment of pathogenicity of Mendelian germline sequence variants. The system allows users to enter the applicable ACMG/AMP-style evidence tags for a specific allele with links to supporting data for each tag and generate guideline-based pathogenicity assessment for the allele. Through automation and comprehensive documentation of evidence codes, the system facilitates more accurate application of the ACMG/AMP guidelines, improves standardization in variant classification, and facilitates collaborative resolution of discordances. The rules of reasoning are configurable with gene-specific or disease-specific guideline variations (e.g. cardiomyopathy-specific frequency thresholds and functional assays). The software is modular, equipped with robust application program interfaces (APIs), and available under a free open source license and as a cloud-hosted web service, thus facilitating both stand-alone use and integration with existing variant curation and interpretation systems. The Pathogenicity Calculator is accessible at http://calculator.clinicalgenome.org . CONCLUSIONS: By enabling evidence-based reasoning about the pathogenicity of genetic variants and by documenting supporting evidence, the Calculator contributes toward the creation of a knowledge commons and more accurate interpretation of sequence variants in research and clinical care.

Digital sustainability: basic conditions for sustainable digital artifacts and their ecosystems.

The modern age has heralded a shift from the industrial society, in which natural resources are crucial input factors for the economy, towards a knowledge society. To date, sustainability literature has treated knowledge-and in particular digital artifacts-mainly as a means to the end of achieving sustainable development. In this conceptual paper, we argue that digital artifacts themselves ought also to be considered as resources, which also need to be sustainable. While over-consumption is a problem facing natural resources, with sustainable digital artifacts, underproduction, and underuse are the biggest challenges. In our view, the sustainability of digital artifacts improves their potential impact on sustainable development. A theoretical foundation for digital artifacts and their ecosystem allows us to present the relevant research on digital information, knowledge management, digital goods, and innovation literature. Based on these insights, we propose ten basic conditions for sustainable digital artifacts and their ecosystem to ensure that they provide the greatest possible benefit for sustainable development. We then apply those characteristics to four exemplary cases: Linux kernel development, Bitcoin cryptocurrency, the Wikipedia project, and the Linking Open Drug Data repositories. The paper concludes with a research agenda identifying topics for sustainability scholars and information systems academics, as well as practitioners. A number of suggestions for future studies on digital sustainability are also put forward.