Sharing Research Data and Intellectual Property Law: A Primer

Measuring the Impact of Data Sharing: From Author-Level Metrics to Quantification of Economic and Non-tangible Benefits

In early 2023, the National Institutes of Health (NIH) implemented its Data Management and Sharing (DMS) Policy, requiring researchers to share scientific data produced with NIH funding. The policy's objective is to amplify the benefits of public investment in research by promoting the dissemination and reusability of primary data. Given this backdrop, identifying a robust methodology to assess the impact of data sharing across diverse research domains is essential. In this review, we adopted two methodological paradigms, the bottom-up and top-down strategies, and employed content analysis to pinpoint established methodologies and innovative practices within this intricate field. Although numerous author-level metrics are available to gauge the impact of data sharing, their application is still limited. Non-traditional metrics, encompassing economic (e.g., cost savings) and intangible benefits, presently appear to hold more potential for evaluating the impact of primary data sharing. Finally, we address the primary obstacles encountered by open data policies and introduce an innovative "Shared model for shared data" framework to bolster data sharing practices and refine evaluation metrics.

Computational Audiology: New Approaches to Advance Hearing Health Care in the Digital Age

The global digital transformation enables computational audiology for advanced clinical applications that can reduce the global burden of hearing loss. In this article, we describe emerging hearing-related artificial intelligence applications and argue for their potential to improve access, precision, and efficiency of hearing health care services. Also, we raise awareness of risks that must be addressed to enable a safe digital transformation in audiology. We envision a future where computational audiology is implemented via interoperable systems using shared data and where health care providers adopt expanded roles within a network of distributed expertise. This effort should take place in a health care system where privacy, responsibility of each stakeholder, and patients' safety and autonomy are all guarded by design.

Data Usage and the Legal Stability of Transactions for the Commercial Operation of Autonomous Vessels Based on Digital Ownership in Korean Civil Law

Stakeholders in the maritime industry have agreed to expand commercial operations by developing autonomous vessels, the epitome of innovative technologies. However, they are still concerned about the risks of infringing on the rights and interests of individuals or organizations linked to data transactions. Based on Locke’s theory of property ownership, and the assurance of absolute ownership as specified in the Constitution of the Republic of Korea, the business model is still in its early stages. This study examined the concept, transaction structure, and application scope of data activating digital platforms to support data transactions, and aid in advancing the new business sector for commercial operations of maritime autonomous surface ships (MASSs). Consequently, this study contributes to and recognizes the future value of knowledge and intellectual property related to maritime data. This is achieved by defining the intellectual property emerging from newer avenues, such as MASSs, blockchain technology, and smart ports, that are consequential to the rapid development of the maritime industry.

Open science in psychophysiology: An overview of challenges and emerging solutions

The present review is the result of a one-day workshop on open science, held at the Annual Meeting of the Society for Psychophysiological Research in Washington, DC, September 2019. The contributors represent psychophysiological researchers at different career stages and from a wide spectrum of institutions. The state of open science in psychophysiology is discussed from different perspectives, highlighting key challenges, potential benefits, and emerging solutions that are intended to facilitate open science practices. Three domains are emphasized: data sharing, preregistration, and multi-site studies. In the context of these broader domains, we present potential implementations of specific open science procedures such as data format harmonization, power analysis, data, presentation code and analysis pipeline sharing, suitable for psychophysiological research. Practical steps are discussed that may be taken to facilitate the adoption of open science practices in psychophysiology. These steps include (1) promoting broad and accessible training in the skills needed to implement open science practices, such as collaborative research and computational reproducibility initiatives, (2) establishing mechanisms that provide practical assistance in sharing of processing pipelines, presentation code, and data in an efficient way, and (3) improving the incentive structure for open science approaches. Throughout the manuscript, we provide references and links to available resources for those interested in adopting open science practices in their research.

A brief guide to the science and art of writing manuscripts in biomedicine

Publishing articles in international scientific journals is the primary method for the communication of validated research findings and ideas. Journal articles are commonly used as a major input for evaluations of researchers and institutions. Few articles have been published previously about the different aspects needed for writing high-quality articles. In this manuscript, we provide an updated and brief guide for the multiple dimensions needed for writing manuscripts in the health and biological sciences, from current, international and interdisciplinary perspectives and from our expertise as authors, peer reviewers and editors. We provide key suggestions for writing major sections of the manuscript (e.g. title, abstract, introduction, methods, results and discussion), for submitting the manuscript and bring an overview of the peer review process and  of the post-publication impact of the articles.

Perspectives for early-career researchers on plagiarism and scientific integrity

Lapses in scientific integrity, such as plagiarism, persist in the scientific realm. To be successful and contributory, early-career researchers (ECRs), including graduate students, need to be able to effectively navigate the literature, peer-review process, and scientific research with integrity. Here we discuss different aspects of scientific integrity related to ECRs. Our discussion centres on the concepts of plagiarism and intellectual property, predatory journals, aspects of peer review, transparency in publishing, and false advanced accreditations. Negative elements within these topics may be especially damaging to ECRs, who may be less familiar with the research landscape. We highlight the need for ECRs to approach scientific investigation cautiously and thoughtfully to promote integrity through critical thinking.

Licensing FAIR Data for Reuse

The last letter of the FAIR acronym stands for Reusability. Data and metadata should be made available with a clear and accessible usage license. But, what are the choices? How can researchers share data and allow reusability? Are all the licenses available for sharing content suitable for data? Data can be covered by different layers of copyright protection making the relationship between data and copyright particularly complex. Some research data can be considered as a work and therefore covered by full copyright while other data can be in the public domain due to their lack of originality. Moreover, a collection of data can be protected by special rights in Europe to acknowledge the investment in time and money in obtaining, presenting, arranging or verifying the data. The need of using a license when sharing data comes from the fact that, under current copyright laws, when rights exist, the absence of any legal notice must be understood as the default “all rights reserved” regime. Unless an exception applies, the authorisation of right holders is necessary for reuse. Right holders could use any text to state the reusability of data but it is advisable to use some of the existing licenses, and especially the ones that are suitable for data and databases. We hope that with this paper we can bring some clarity in relation to the rights involved when sharing research data.

ASTRO Journals' Data Sharing Policy and Recommended Best Practices

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed.

Scientific Data Management in the Age of Big Data: An Approach Supporting a Resilience Index Development Effort

The increased availability of publicly available data is, in many ways, changing our approach to conducting research. Not only are cloud-based information resources providing supplementary data to bolster traditional scientific activities (e.g., field studies, laboratory experiments), they also serve as the foundation for secondary data research projects such as indicator development. Indicators and indices are a convenient way to synthesize disparate information to address complex scientific questions that are difficult to measure directly (e.g., resilience, sustainability, well-being). In the current literature, there is no shortage of indicator or index examples derived from secondary data with a growing number that are scientifically focused. However, little information is provided describing the management approaches and best practices used to govern the data underpinnings supporting these efforts. From acquisition to storage and maintenance, secondary data research products rely on the availability of relevant, high-quality data, repeatable data handling methods and a multi-faceted data flow process to promote and sustain research transparency and integrity. The U.S. Environmental Protection Agency recently published a report describing the development of a climate resilience screening index which used over one million data points to calculate the final index. The pool of data was derived exclusively from secondary sources such as the U.S. Census Bureau, Bureau of Labor Statistics, Postal Service, Housing and Urban Development, Forestry Services and others. Available data were presented in various forms including portable document format (PDF), delimited ASCII and proprietary format (e.g., Microsoft Excel, ESRI ArcGIS). The strategy employed for managing these data in an indicator research and development effort represented a blend of business practices, information science, and the scientific method. This paper describes the approach, highlighting key points unique for managing the data assets of a smaller scale research project in an era of "big data."

Data sharing in psychology

Routine data sharing, defined here as the publication of the primary data and any supporting materials required to interpret the data acquired as part of a research study, is still in its infancy in psychology, as in many domains. Nevertheless, with increased scrutiny on reproducibility and more funder mandates requiring sharing of data, the issues surrounding data sharing are moving beyond whether data sharing is a benefit or a bane to science, to what data should be shared and how. Here, we present an overview of these issues, specifically focusing on the sharing of so-called "long tail" data, that is, data generated by individual laboratories as part of largely hypothesis-driven research. We draw on experiences in other domains to discuss attitudes toward data sharing, cost-benefits, best practices and infrastructure. We argue that the publishing of data sets is an integral component of 21st-century scholarship. Moreover, although not all issues around how and what to share have been resolved, a consensus on principles and best practices for effective data sharing and the infrastructure for sharing many types of data are largely in place. (PsycINFO Database Record

How ownership rights over microorganisms affect infectious disease control and innovation: A root-cause analysis of barriers to data sharing as experienced by key stakeholders

BACKGROUND

Genetic information of pathogens is an essential input for infectious disease control, public health and for research. Efficiency in preventing and responding to global outbreaks relies on timely access to such information. Still, ownership barriers stand in the way of timely sharing of genetic data from pathogens, frustrating efficient public health responses and ultimately the potential use of such resources in innovations. Under a One Health approach, stakeholders, their interests and ownership issues are manifold and need to be investigated. We interviewed key actors from governmental and non-governmental bodies to identify overlapping and conflicting interests, and the overall challenges for sharing pathogen data, to provide essential inputs to the further development of political and practical strategies for improved data sharing practices.

METHODS & FINDINGS

To identify and prioritize barriers, 52 Key Opinion Leaders were interviewed. A root-cause analysis was performed to identify causal relations between barriers. Finally, barriers were mapped to the innovation cycle reflecting how they affect the range of surveillance, innovation, and sharing activities. Four main barrier categories were found: compliance to regulations, negative consequences, self-interest, and insufficient incentives for compliance. When grouped in sectors (research institutes, public health organizations, supra-national organizations and industry) stakeholders appear to have similar interests, more than when grouped in domains (human, veterinary and food). Considering the innovation process, most of barriers could be mapped to the initial stages of the innovation cycle as sampling and sequencing phases. These are stages of primary importance to outbreak control and public health response. A minority of barriers applied to later stages in the innovation cycle, which are of more importance to product development.

CONCLUSION

Overall, barriers are complex and entangled, due to the diversity of causal factors and their crosscutting features. Therefore, barriers must be addressed in a comprehensive and integrated manner. Stakeholders have different interests highlighting the diversity in motivations for sharing pathogen data: prioritization of public health, basic research, economic welfare and/or innovative capacity. Broad inter-sectorial discussions should start with the alignment of these interests within sectors. The improved sharing of pathogen data, especially in upstream phases of the innovation process, will generate substantial public health benefits through increased availability of data to inform surveillance systems, as well as to allow the (re-)use of data for the development of medical countermeasures to control infectious diseases.

Les données et leurs impacts théoriques et pratiques sur les professionnels de l’information

Les données sont présentes dans l’environnement informationnel actuel sous différentes formes : données confidentielles commerciales ou gouvernementales, mégadonnées, données ouvertes des gouvernements, données ouvertes liées (Linked Open Data) du Web sémantique. Comment les professionnels de l’information devraient-ils se préparer pour traiter ces divers types de données ? Nous proposons que cette préparation repose sur trois éléments : une connaissance éclairée des différents types de données en jeu, une initiation aux ressources nécessaires pour traiter chaque type et une compréhension de l’impact qu’aura chacun sur la discipline des sciences de l’information et sur la pratique des professionnels de l’information.

The Design, Development, and Evaluation of a Qualitative Data Collection Application for Pregnant Women

PURPOSE

This article explores the development and evaluation of a smartphone mobile software application (app) to collect qualitative data. The app was specifically designed to capture real-time qualitative data from women planning a vaginal birth after caesarean delivery. This article outlines the design and development of the app to include funding, ethics, and the recruitment of an app developer, as well as the evaluation of using the app by seven participants.

ORGANIZING CONSTRUCT

Data collection methods used in qualitative research include interviews and focus groups (either online, face-to-face, or by phone), participant diaries, or observations of interactions. This article identifies an alternative data collection methodology using a smartphone app to collect real-time data.

CONCLUSIONS

The app provides real-time data and instant access to data alongside the ability to access participants from a variety of locations. This allows the researcher to gain insight into the experiences of participants through audio or video recordings in longitudinal studies without the need for constant interactions or interviews with participants.

CLINICAL RELEVANCE

Using smartphone applications can allow researchers to access participants who are traditionally hard to reach and access their data in real time. Evaluating these apps before use in research is invaluable.

Product Development and Commercialization of Diagnostic or Life Science Products for Scientists and Researchers

Commercializing a diagnostic or life science product often encompasses different goals than that of research and grant funding. There are several necessary steps, and a strategy needs to be well defined in order to be successful. Product development requires input from and between various groups within a company and, for academia, outside entities. The product development stakeholder groups/entities are research, marketing, development, regulatory, manufacturing, clinical, safety/efficacy, and quality. After initial research and development, much of the work in product development can be outsourced or jointly created using public-private partnerships. This chapter serves as an overview of the product development process and provides a guide to best define a product strategy.

A Complete Overhaul of the Electron Energy-Loss Spectroscopy and X-Ray Absorption Spectroscopy Database: eelsdb.eu

The electron energy-loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) database has been completely rewritten, with an improved design, user interface, and a number of new tools. The database is accessible at https://eelsdb.eu/ and can now be used without registration. The submission process has been streamlined to encourage spectrum submissions and the new design gives greater emphasis on contributors' original work by highlighting their papers. With numerous new filters and a powerful search function, it is now simple to explore the database of several hundred EELS and XAS spectra. Interactive plots allow spectra to be overlaid, facilitating online comparison. An application-programming interface has been created, allowing external tools and software to easily access the information held within the database. In addition to the database itself, users can post and manage job adverts and read the latest news and events regarding the EELS and XAS communities. In accordance with the ongoing drive toward open access data increasingly demanded by funding bodies, the database will facilitate open access data sharing of EELS and XAS spectra.