25 papers · ranked by Valyu relevance
Visara Urovi, Vikas Jaiman, Arno Angerer, Michel Dumontier
Easy access to data is one of the main avenues to accelerate scientific research. As a key element of scientific innovations, data sharing allows the reproduction of results, helps prevent data fabrication, falsification, and misuse. Although the research benefits from data reuse are widely acknowledged, the data…
Juha-Pekka Soininen, Gabriella Laatikainen
The paper presents a use case model and a logical architecture model of a data space system. The models view the data space system from the user and operator perspectives and describe the needed functionalities and their connection on an abstract level. The core features in our data space model are collaboration…
Zhenqi Wang, Shaopeng Guan, Sitharthan Ramachandran
The traditional data-sharing model relies on a centralized third-party platform, which presents challenges such as poor transaction transparency and unsecured data security. In this article, we propose a blockchain-based traceable and secure data-sharing scheme. Firstly, we designed an attribute encryption-based method…
Annelize G Nienaber McKay, Dirk Brand, Marietjie Botes, Nezerith Cengiz + 1 more
'Nezerith Cengiz' 'Marno Swart'] Title: Abstract The sharing of health data is an essential component in the provision of healthcare, in medical research, and disease surveillance. Health data sharing is subject to regulatory frameworks that vary across jurisdictions. In Africa, numerous factors complicate the…
Tsaone Tamuhla, Eddie T Lulamba, Themba Mutemaringa, Nicki Tiffin
Evidence-based healthcare relies on health data from diverse sources to inform decision-making across different domains, including disease prevention, aetiology, diagnostics, therapeutics and prognosis. Increasing volumes of highly granular data provide opportunities to leverage the evidence base, with growing…
Lam Duc Nguyen, James Hoang, Qin Wang, Qinghua Lu + 2 more
'Shiping Chen'] Abstract—Across industries, there is an ever-increasing rate of data sharing for collaboration and innovation between organizations and their customers, partners, suppliers, and internal teams. However, many enterprises are restricted from freely sharing data due to regulatory restrictions across…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…
Herve Emissah, Bengt Ljungquist, Giorgio A. Ascoli
Neural morphology, the branching geometry of neurons and glia in the nervous system, is an essential cellular substrate of brain function and pathology. Despite the accelerating production of digital reconstructions of neural morphology in laboratories worldwide, the public accessibility of data remains a core issue in…
Haya Deeb, Hwee Yun Wong, Trisha Usman, Megan A. M. Kutzer + 2 more
The evolution of research practices emphasizes the role of Open Data in fostering transparency and collaboration. This study evaluates the adoption of Open Data practices in the School of Biological Sciences at a research-intensive university in the United Kingdom. Our analysis of research data sharing from 2014 to…
Christine L. Borgman, Paul Groth
| 1 | Why, when, how, and for whom should data be shared? | 2 | | --- | --- | --- | | 2 | Creating, Sharing, and Reusing Data | 4 | | 3 | Dimensions of Distance between Data Creators and Data Reusers | 5 | | 3.1 | Domain Distance | 5 | | | 3.1.1 Social aspects of domain distance | 5 | | | 3.1.2 Technical aspects of…
Christian Paret, Nike Unverhau, Franklin Feingold, Russell A. Poldrack + 3 more
Replicability and reproducibility of scientific findings is paramount for sustainable progress in neuroscience. Preregistration of the hypotheses and methods of an empirical study before analysis, the sharing of primary research data, and compliance with data standards such as the Brain Imaging Data Structure (BIDS)…
Arthur W. Toga, Sidney Taiko Sheehan, Tyler Ard
Data sharing in scientific research is widely acknowledged as crucial for accelerating progress and innovation. Mandates from funders, such as the NIH’s updated Data Sharing Policy, have been beneficial in promoting data sharing. However, the effectiveness of such mandates relies heavily on the motivation of data…
Kylie E. Hunter, Aidan C. Tan, Angela C. Webster, Daniel G. Hamilton + 9 more
5.1### Responsibility: Avoid misinterpretation of the data and misleading secondary analyses Researchers are often concerned that data recipients will incorrectly interpret their study data or, intentionally or unintentionally, conduct inappropriate or misleading secondary analyses. Communication, collaboration and…
Antti Rousi
Without sufficient information about research data practices occurring in a particular research organisation, there is a risk of mismatching research data service efforts with the needs of its researchers. This study describes how data acquiring and data sharing occurring within a particular research organisation can…
Robert L. Grossman, Maryellen L. Giger, Julie Ann Johnson, Jeremy D. Marks + 3 more
'Jeremy D. Marks' 'Jessica P. Ridgway' 'Julian Solway' 'Walter M. Stadler'] Academic medical centers are generating an increasing amount of biomedical data and there is an increasing demand for biomedical data for research purposes by research projects, research consortia, companies, and other third parties. At the…
Christian Wendelborn, Michael Anger, Christoph Schickhardt
Sharing research data has great potential to benefit science and society. However, data sharing is still not common practice. Since public research funding agencies have a particular impact on research and researchers, the question arises: Are public funding agencies morally obligated to promote data sharing? We argue…
Geoff Krause, Madelaine Hare, Michael Smit, Philippe Mongeon
Open data is receiving increased attention and support in academic environments, with one justification being that shared data may be re-used in further research. But what evidence exists for such re-use, and what is the relationship between the producers of shared datasets and researchers who use them? Using a sample…
Nitesh Kumar Sharma, Ram Ayyala, Dhrithi Deshpande, Yesha M Patel + 11 more
Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Laura A. Hug, Roland Hatzenpichler, Cristina Moraru, André Soares + 3 more
Science benefits from rapid, open data sharing but samples for sequencing data are expensive for data creators to acquire and process. Current guidelines for data reuse were established two decades ago, when databases were several million times smaller, necessitating an update. This article presents a roadmap to…
Jason M. Carpenter, Zhi-Li Zhang
The modern data economy is built on sharing data. However, sharing data can be an expensive and risky endeavour. Existing sharing systems like Distributed File Systems provide full read, write, and execute Role-based Access Control (RBAC) for sharing data, but can be expensive and difficult to scale. Likewise such…
Authors not listed
The first step in discovering novel medicines is identifying an initial hit against a biological target or organism, followed by extensive iterative processes to explore the structure-activity relationship and establish a lead compound. As a result, drug discovery laboratories tend to accumulate extensive collections…
David F. Nippa, Alex T. Müller, Kenneth Atz, David B. Konrad + 3 more
Leveraging the increasing volume of chemical reaction data can enhance synthesis planning and improve suc- cess rates. However, machine learning applications for retrosynthesis planning and forward reaction prediction tools depend on having readily available, high-quality data in a structured format. While some public…
Authors not listed
The nanosafety domain has seen significant advancements in data generation and sharing, yet challenges remain in ensuring data interoperability and reuse. This article focuses on developing a semantic interoperability framework for nanosafety data to maximize the FAIRness (Findability, Accessibility, Interoperability…
Frédéric Burdet, Pierre-Marie Allard, Louis-Felix Nothias, Olivier Kirchhoffer + 16 more
Plants have a complex chemo-diversity and represent a reservoir of potential new therapeutic agents. Within a Swiss research project, six scientific research groups from different disciplines are collaborating to investigate a collection of more than 17’000 unique dried plant extracts. It aims to find new bioactive…