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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RDFIO: extending Semantic MediaWiki for interoperable biomedical data management
|
|---|---|
| Published in |
Journal of Biomedical Semantics, September 2017
|
| DOI | 10.1186/s13326-017-0136-y |
| Pubmed ID | |
| Authors |
Samuel Lampa, Egon Willighagen, Pekka Kohonen, Ali King, Denny Vrandečić, Roland Grafström, Ola Spjuth |
| Abstract |
Biological sciences are characterised not only by an increasing amount but also the extreme complexity of its data. This stresses the need for efficient ways of integrating these data in a coherent description of biological systems. In many cases, biological data needs organization before integration. This is not seldom a collaborative effort, and it is thus important that tools for data integration support a collaborative way of working. Wiki systems with support for structured semantic data authoring, such as Semantic MediaWiki, provide a powerful solution for collaborative editing of data combined with machine-readability, so that data can be handled in an automated fashion in any downstream analyses. Semantic MediaWiki lacks a built-in data import function though, which hinders efficient round-tripping of data between interoperable Semantic Web formats such as RDF and the internal wiki format. To solve this deficiency, the RDFIO suite of tools is presented, which supports importing of RDF data into Semantic MediaWiki, with metadata needed to export it again in the same RDF format, or ontology. Additionally, the new functionality enables mash-ups of automated data imports combined with manually created data presentations. The application of the suite of tools is demonstrated by importing drug discovery related data about rare diseases from Orphanet and acid dissociation constants from Wikidata. The RDFIO suite of tools is freely available for download via pharmb.io/project/rdfio . Through a set of biomedical demonstrators, it is demonstrated how the new functionality enables a number of usage scenarios where the interoperability of SMW and the wider Semantic Web is leveraged for biomedical data sets, to create an easy to use and flexible platform for exploring and working with biomedical data. |
X Demographics
The data shown below were collected from the profiles of 16 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 | 3 | 19% |
| Vietnam | 1 | 6% |
| Belgium | 1 | 6% |
| Switzerland | 1 | 6% |
| France | 1 | 6% |
| Spain | 1 | 6% |
| China | 1 | 6% |
| Netherlands | 1 | 6% |
| Sweden | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 5 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 81% |
| Scientists | 3 | 19% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 3% |
| Unknown | 37 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 26% |
| Student > Ph. D. Student | 8 | 21% |
| Student > Doctoral Student | 4 | 11% |
| Student > Master | 4 | 11% |
| Other | 3 | 8% |
| Other | 4 | 11% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 32% |
| Agricultural and Biological Sciences | 8 | 21% |
| Social Sciences | 4 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 8% |
| Medicine and Dentistry | 3 | 8% |
| Other | 3 | 8% |
| Unknown | 5 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 03 October 2019.
All research outputs
#1,456,670
of 25,381,783 outputs
Outputs from Journal of Biomedical Semantics
#7
of 367 outputs
Outputs of similar age
#28,259
of 321,886 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 18 outputs
Altmetric has tracked 25,381,783 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 367 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,886 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.