scholarly journals The Neuroscience Information Framework (NIF): A Unified Semantic Framework and Associated Tools for Discovery, Integration, and Utilization of Biomedical Data and Resources on the Web

2014 ◽  
Vol 8 ◽  
Author(s):  
Grethe Jeffrey ◽  
Bandrowski Anita ◽  
Cachat Jonathan ◽  
Gupta Amarnath ◽  
Imam Fahim ◽  
...  
Keyword(s):  
Biomedical Data ◽  
Semantic Framework ◽  
Information Framework ◽  
Neuroscience Information Framework ◽  
The Web

A Semantic Framework for Touristic Information Systems

2014 ◽  
pp. 166-185
Author(s):  
Salvador Lima ◽  
José Moreira
Keyword(s):  
Relational Databases ◽  
Web Applications ◽  
Ad Hoc ◽  
Information Resources ◽  
Semantic Web Technologies ◽  
Semantic Framework ◽  
Layered Architecture ◽  
Description Framework ◽  
Automated Processes ◽  
The Web

The Web is a crucial means for the dissemination of touristic information. However, most touristic information resources are stored directly in Web pages or in relational databases that are accessible through ad-hoc Web applications, and the use of automated processes to search, extract and interpret information can hardly be implemented. The Semantic Web technologies, aiming at representing the background knowledge about Web resources in a computational way, can be an important contribution to the development of such automated processes. This chapter introduces the concept of touristic object, giving special attention to the representation of temporal, spatial, and thematic knowledge. It also proposes a three-layered architecture for the representation of touristic objects in the Web. The central part is the domain layer, defining a Semantic Model for Tourism (SeMoT) to describe concepts, relationships, and constraints using ontologies. The data layer supports the mapping of touristic information in relational databases into Resource Description Framework (RDF) virtual graphs following the SeMoT specification. The application layer deals with the integration of information from different data sources into a unified knowledge model, offering a common vocabulary to describe touristic information resources. Finally, we also show how to use this framework for planning touristic itineraries.

scholarly journals Linking Educational Resources on Data Science

2019 ◽  
Vol 33 ◽  
pp. 9404-9409
Author(s):  
José Luis Ambite ◽  
Jonathan Gordon ◽  
Lily Fierro ◽  
Gully Burns ◽  
Joel Mathew
Keyword(s):  
Big Data ◽  
Linked Data ◽  
Data Science ◽  
Resource Discovery ◽  
Educational Resources ◽  
Machine Learning Techniques ◽  
Biomedical Data ◽  
Centers Of Excellence ◽  
Training Resources ◽  
The Web

The availability of massive datasets in genetics, neuroimaging, mobile health, and other subfields of biology and medicine promises new insights but also poses significant challenges. To realize the potential of big data in biomedicine, the National Institutes of Health launched the Big Data to Knowledge (BD2K) initiative, funding several centers of excellence in biomedical data analysis and a Training Coordinating Center (TCC) tasked with facilitating online and inperson training of biomedical researchers in data science. A major initiative of the BD2K TCC is to automatically identify, describe, and organize data science training resources available on the Web and provide personalized training paths for users. In this paper, we describe the construction of ERuDIte, the Educational Resource Discovery Index for Data Science, and its release as linked data. ERuDIte contains over 11,000 training resources including courses, video tutorials, conference talks, and other materials. The metadata for these resources is described uniformly using Schema.org. We use machine learning techniques to tag each resource with concepts from the Data Science Education Ontology, which we developed to further describe resource content. Finally, we map references to people and organizations in learning resources to entities in DBpedia, DBLP, and ORCID, embedding our collection in the web of linked data. We hope that ERuDIte will provide a framework to foster open linked educational resources on the Web.

A Decision Support System (DSS) for Colorectal Cancer Follow-Up Program via a Semantic Framework

2015 ◽  
Vol 10 (1) ◽  
pp. 17-38 ◽  
Author(s):  
Kalpdrum Passi ◽  
Hongtao Zhao
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
Decision Support ◽  
Cancer Patients ◽  
Support System ◽  
Web Application ◽  
Semantic Framework ◽  
Follow Up Care ◽  
The Web

This paper offers insights into evolving a decision support system (DSS) to aid primary care physicians and/or nurses in the post-surgical care of patients with Colorectal Cancer in a clinical setting. Presently, the oncologists in the cancer center, who are familiar with the Clinical Practice Guidelines (CPGs), are primarily responsible for the provision of follow-up care to their patients on the basis of the CPGs; in contrast, the attending primary care physician and/or nurse assisting the oncologist may be unfamiliar with these guidelines. These caregivers would, therefore, either require hardcopies of the CPGs or can be aided via a DSS for them to be able to provide the appropriate follow-up care for the respective cancer patients. Clearly, the Colorectal Cancer follow-up CPGs have to be analyzed and the ontology representing the knowledge embedded in the guidelines designed prior to realizing such a DSS. The designed ontology is often coded into Web Ontology Language (OWL) as a standard ontology that can be accessed through the Web. The authors' research team designed and presented the semantic framework of the web application, using the designed ontology that combines the current Web technology with database storage to achieve a unified development of the DSS. The authors also designed a user-friendly interface of the Web application to provide medical practitioners the functionality of the CPGs and the flexibility to customize the desired follow-up care schedule. The resulting DSS provides the physicians with follow-up program for the Colorectal Cancer patients based on the CPGs. The system was built using the semantic framework for the follow-up program and queries on the system are executed through SPARQL query engine.

A Study on Family Medical Sensor Networks and ECG and Temperature Monitoring Node Based on 6LoWPAN

2012 ◽  
Vol 472-475 ◽  
pp. 3445-3449
Author(s):  
Wei Fu ◽  
Meng Ling Shui ◽  
Ping Wang
Keyword(s):  
Sensor Networks ◽  
Sensor Node ◽  
Medical Service ◽  
Temperature Monitoring ◽  
Sensor Nodes ◽  
The Internet ◽  
Health Record ◽  
Biomedical Data ◽  
Medical Sensor Networks ◽  
The Web

By using advanced IPv6 technology, This paper presents a design of family wireless medical sensor networks(WMSN) and a implementation of ECG and temperature monitoring sensor node. The 6LoWPAN medical sensor nodes can add into the WMSN rapidly and the biomedical data are routed into the Internet through the gateway, therefore, it can get the information of health record on the web expediently and simply. In addition, this paper proposes a scheme of telemedicine for convenient and secure medical service.

scholarly journals Assessing value of biomedical digital repositories

2017 ◽  
Author(s):  
Chun-Nan Hsu ◽  
Anita Bandrowski ◽  
Jeffrey S. Grethe ◽  
Maryann E. Martone
Keyword(s):  
Research Community ◽  
Digital Repository ◽  
Digital Repositories ◽  
Data Citation ◽  
Funding Agencies ◽  
Quality Aspects ◽  
Resource Identification ◽  
Citation Practices ◽  
Information Framework ◽  
Neuroscience Information Framework

Digital repositories bring direct impact and influence on the research community and society but measuring their value using formal metrics remains challenging. their value. It is challenging to define a single perfect metric that covers all quality aspects. Here, we distinguish here between impact and influence and discuss measures and mentions as the basis of quality metrics of a digital repository. We argue that these challenges may potentially be overcome through the introduction of standard resource identification and data citation practices. We briefly summarize our research and experience in the Neuroscience Information Framework, the BD2K BioCaddie project on data citation, and the Resource Identification Initiative. Full implementation of these standards will depend on cooperation from all stakeholders --- digital repositories, authors, publishers, and funding agencies, but both resource and data citation have been gaining support with researchers and publishers.

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