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Attention Score in Context
| Title |
Data Ontology and an Information System Realization for Web-Based Management of Image Measurements
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, January 2011
|
| DOI | 10.3389/fninf.2011.00025 |
| Pubmed ID | |
| Authors |
Dimiter Prodanov |
| Abstract |
Image acquisition, processing, and quantification of objects (morphometry) require the integration of data inputs and outputs originating from heterogeneous sources. Management of the data exchange along this workflow in a systematic manner poses several challenges, notably the description of the heterogeneous meta-data and the interoperability between the software used. The use of integrated software solutions for morphometry and management of imaging data in combination with ontologies can reduce meta-data loss and greatly facilitate subsequent data analysis. This paper presents an integrated information system, called LabIS. The system has the objectives to automate (i) the process of storage, annotation, and querying of image measurements and (ii) to provide means for data sharing with third party applications consuming measurement data using open standard communication protocols. LabIS implements 3-tier architecture with a relational database back-end and an application logic middle tier realizing web-based user interface for reporting and annotation and a web-service communication layer. The image processing and morphometry functionality is backed by interoperability with ImageJ, a public domain image processing software, via integrated clients. Instrumental for the latter feat was the construction of a data ontology representing the common measurement data model. LabIS supports user profiling and can store arbitrary types of measurements, regions of interest, calibrations, and ImageJ settings. Interpretation of the stored measurements is facilitated by atlas mapping and ontology-based markup. The system can be used as an experimental workflow management tool allowing for description and reporting of the performed experiments. LabIS can be also used as a measurements repository that can be transparently accessed by computational environments, such as Matlab. Finally, the system can be used as a data sharing tool. |
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% |
| Switzerland | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 8% |
| Japan | 1 | 4% |
| Unknown | 21 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 50% |
| Student > Ph. D. Student | 4 | 17% |
| Student > Bachelor | 3 | 13% |
| Professor > Associate Professor | 2 | 8% |
| Student > Master | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 29% |
| Agricultural and Biological Sciences | 6 | 25% |
| Engineering | 4 | 17% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Neuroscience | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 06 January 2012.
All research outputs
#18,313,878
of 22,675,759 outputs
Outputs from Frontiers in Neuroinformatics
#622
of 742 outputs
Outputs of similar age
#159,968
of 180,328 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#18
of 24 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 742 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.