| Title |
SCALEUS: Semantic Web Services Integration for Biomedical Applications
|
|---|---|
| Published in |
Journal of Medical Systems, February 2017
|
| DOI | 10.1007/s10916-017-0705-8 |
| Pubmed ID | |
| Authors |
Pedro Sernadela, Lorena González-Castro, José Luís Oliveira |
| Abstract |
In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ . |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 38 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 23% |
| Student > Master | 7 | 18% |
| Researcher | 5 | 13% |
| Student > Bachelor | 4 | 10% |
| Student > Doctoral Student | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 44% |
| Agricultural and Biological Sciences | 6 | 15% |
| Medicine and Dentistry | 3 | 8% |
| Engineering | 2 | 5% |
| Social Sciences | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 February 2017.
All research outputs
#14,796,471
of 22,955,959 outputs
Outputs from Journal of Medical Systems
#622
of 1,157 outputs
Outputs of similar age
#184,964
of 310,174 outputs
Outputs of similar age from Journal of Medical Systems
#11
of 18 outputs
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