Cloud-Based Semantic Data Management for the VPH-Share Medical Research Community

2014 ◽  
Author(s):  
Siegfried Benkner ◽  
Chris Borckholder ◽  
Yuriy Kaniovskyi Alfredo Saglimbeni ◽  
Tomas Pariente Lobo ◽  
Piotr Nowakowski ◽  
...  
Keyword(s):  
Data Management ◽  
Medical Research ◽  
Research Community ◽  
Semantic Data

Framework for Biosignal Interpretation in Intensive Care and Anesthesia

1997 ◽  
Vol 36 (04/05) ◽  
pp. 340-344 ◽  
Author(s):  
I. Korhonen ◽  
M. van Gils ◽  
A. Kari ◽  
N. Saranummi
Keyword(s):  
Critical Care ◽  
Intensive Care ◽  
Data Management ◽  
Clinical Evaluation ◽  
Patient Monitoring ◽  
Research Community ◽  
Clinical Routine ◽  
The Poor ◽  
Outcomes Of Care

Abstract:Improved monitoring improves outcomes of care. As critical care is “critical”, everything that can be done to detect and prevent complications as early as possible benefits the patients. In spite of major efforts by the research community to develop and apply sophisticated biosignal interpretation methods (BSI), the uptake of the results by industry has been poor. Consequently, the BSI methods used in clinical routine are fairly simple. This paper postulates that the main reason for the poor uptake is the insufficient bridging between the actors (i.e., clinicians, industry and research). This makes it difficult for the BSI developers to understand what can be implemented into commercial systems and what will be accepted by clinicians as routine tools. A framework is suggested that enables improved interaction and cooperation between the actors. This framework is based on the emerging commercial patient monitoring and data management platforms which can be shared and utilized by all concerned, from research to development and finally to clinical evaluation.

Features and Limitations of Ontologies for Coronavirus Data Management in Libraries

2021 ◽  
pp. 18-40
Author(s):  
Enrique Wulff
Keyword(s):  
Semantic Web ◽  
Data Management ◽  
Quality Criteria ◽  
Emerging Technology ◽  
Data Sources ◽  
Semantic Data ◽  
Important Quality ◽  
Selection For ◽  
Over Time ◽  
Or Applications

The purpose of this chapter is to follow the evolution of what has occurred over time in the ontologies published in response to the COVID-19 pandemic. Correctness and completeness of ontologies on the schema and instance level are important quality criteria in their selection for an application. To help both the librarians and the users, there is a need of a framework for the comparison of different semantic data sources in the COVID-19 pandemic. Meanwhile, online services and/or applications based on ontologies or SKOS-based COVID-19 thesauri are still rare. As an emerging technology in libraries, an all-integrating ontology for coronavirus disease knowledge and data refers to the continuing development of an existing technology. In spite of using ontologies in the Semantic Web, meanings of concepts and relationships are still largely unrealized in terms of obtaining accurate and timely information about COVID-19. But the nature of causal relationships on this disease is made accessible through ontologies as the material in which its main concepts are supported.

Occupational Health in the Developing World: A Role for the Medical Research Community?

2007 ◽  
Vol 49 (11) ◽  
pp. 1184-1188 ◽  
Author(s):  
Gabriela Salmon Mulanovich ◽  
Andres G. Lescano ◽  
Víctor E. Gonzaga ◽  
David L. Blazes
Keyword(s):  
Occupational Health ◽  
Medical Research ◽  
Developing World ◽  
Research Community

scholarly journals Expressing the Tacit Knowledge of a Digital Library System as Linked Data

Computers ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 49 ◽  
Author(s):  
Angela Di Iorio ◽  
Marco Schaerf
Keyword(s):  
Data Management ◽  
Tacit Knowledge ◽  
Digital Library ◽  
Linked Data ◽  
Data Publishing ◽  
Library System ◽  
Semantic Data ◽  
Digital Library System ◽  
Interpretation Process ◽  
Data Source

Library organizations have enthusiastically undertaken semantic web initiatives and in particular the data publishing as linked data. Nevertheless, different surveys report the experimental nature of initiatives and the consumer difficulty in re-using data. These barriers are a hindrance for using linked datasets, as an infrastructure that enhances the library and related information services. This paper presents an approach for encoding, as a Linked Vocabulary, the “tacit” knowledge of the information system that manages the data source. The objective is the improvement of the interpretation process of the linked data meaning of published datasets. We analyzed a digital library system, as a case study, for prototyping the “semantic data management” method, where data and its knowledge are natively managed, taking into account the linked data pillars. The ultimate objective of the semantic data management is to curate the correct consumers’ interpretation of data, and to facilitate the proper re-use. The prototype defines the ontological entities representing the knowledge, of the digital library system, that is not stored in the data source, nor in the existing ontologies related to the system’s semantics. Thus we present the local ontology and its matching with existing ontologies, Preservation Metadata Implementation Strategies (PREMIS) and Metadata Objects Description Schema (MODS), and we discuss linked data triples prototyped from the legacy relational database, by using the local ontology. We show how the semantic data management, can deal with the inconsistency of system data, and we conclude that a specific change in the system developer mindset, it is necessary for extracting and “codifying” the tacit knowledge, which is necessary to improve the data interpretation process.

scholarly journals Towards Growing a COIN in a Medical Research Community

2011 ◽  
Vol 26 ◽  
pp. 3-16 ◽  
Author(s):  
Peter A. Gloor ◽  
Francesca Grippa ◽  
Amy Borgert ◽  
Richard B. Colletti ◽  
George Dellal ◽  
...  
Keyword(s):  
Medical Research ◽  
Research Community

scholarly journals Andrewes's christmas fairy tale: atypical thinking about cancer aetiology in 1935

2016 ◽  
Vol 70 (2) ◽  
pp. 175-201 ◽  
Author(s):  
Neeraja Sankaran ◽  
Ton van Helvoort
Keyword(s):  
Medical Research ◽  
Fairy Tale ◽  
Medical Science ◽  
Research Community ◽  
History Of Ideas ◽  
International Medical Research ◽  
Viral Aetiology ◽  
History Of ◽  
Fairy Story

This paper uses a short ‘Christmas fairy-story for oncologists’ sent by Christopher Andrewes with a 1935 letter to Peyton Rous as the centrepiece of a reflection on the state of knowledge and speculation about the viral aetiology of cancer in the 1930s. Although explicitly not intended for public circulation at the time, the fairy-story merits publication for its significance in the history of ideas about viruses, which are taken for granted today. Andrewes and Rous were prominent members of the international medical research community and yet faced strong resistance to their theory that viruses could cause such tumours as chicken sarcomas and rabbit papillomas. By looking at exchanges between these men among themselves and other proponents of their theories and with their oncologist detractors, we highlight an episode in the behind-the-scenes workings of medical science and show how informal correspondence helped keep alive a vital but then heterodox idea about the role of viruses in causing cancer.

scholarly journals 11,000 researchers gave their views on data sharing, here's what we learned

2019 ◽  
Author(s):  
Mithu Lucraft ◽  
Samuel Winthrop
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Market Research ◽  
Open Data ◽  
White Paper ◽  
Research Community ◽  
Data Publishing ◽  
Training And Education ◽  
Collaborative Action ◽  
Share Data

Good data sharing can make research more productive, more likely to be cited, and unlock innovation for the good of society. In 2019, a Springer Nature white paper (Lucraft et al. 2019), based on surveys with more than 11,000 researchers internationally, set out key challenges in data management and data sharing. We found: Data sharing is increasing: more than 64% of researchers in a 2018 survey said they made their data openly available. The majority of researchers see data sharing as important: across three surveys, when asked about the importance of making data discoverable, researchers gave an average rating of 7.5 out of 10. Data sharing and planning is currently suboptimal: The majority of the research community are not yet managing or sharing data in ways that make it findable, accessible or reusable. Increasingly, funders and other expert groups (European Commission 2018) are emphasising the need for data that is FAIR (findable, accessible, interoperable and re-useable). To shift the needle on data sharing and to reap the benefits from more widely-available open data, collaborative action is required. In this presentation, we will discuss the five measures we believe are needed to make data sharing the norm: Clear policy: from funders, institutions, journals/publishers, and research communities themselves. Better credit: to make data sharing worth a researcher’s time. Explicit funding: for data management and data sharing, as well as data publishing. Practical help: for organising data, finding appropriate repositories, and provision of faster, easier routes to share data. Training and education: to answer common questions from researchers on data sharing and to help build skills and knowledge. We will draw on evidence and case studies from across Europe and beyond, as well as further feedback from our market research.

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