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Integrating databases for research on health and performance in small animals and horses in the Nordic countries

Overview of attention for article published in Acta Veterinaria Scandinavica, June 2011
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Title
Integrating databases for research on health and performance in small animals and horses in the Nordic countries
Published in
Acta Veterinaria Scandinavica, June 2011
DOI 10.1186/1751-0147-53-s1-s4
Pubmed ID
Authors

Agneta Egenvall, Ane Nødtvedt, Lars Roepstorff, Brenda Bonnett

Abstract

In a world of limited resources, using existing databases in research is a potentially cost-effective way to increase knowledge, given that correct and meaningful results are gained.Nordic examples of the use of secondary small animal and equine databases include studies based on data from tumour registries, breeding registries, young horse quality contest results, competition data, insurance databases, clinic data, prescription data and hunting ability tests. In spite of this extensive use of secondary databases, integration between databases is less common. The aim of this presentation is to briefly review key papers that exemplify different ways of utilizing data from multiple sources, to highlight the benefits and limitations of the approaches, to discuss key issues/challenges that must be addressed when integrating data and to suggest future directions. Data from pedigree databases have been individually merged with competition data and young horse quality contest data, and true integration has also been done with canine insurance data and with equine clinical data. Data have also been merged on postal code level; i.e. insurance data were merged to a digitized map of Sweden and additional meteorological information added. In addition to all the data quality and validity issues inherent in the use of a single database, additional obstacles arise when combining information from several databases. Loss of individuals due to incorrect or mismatched identifying information can be considerable. If there are any possible biases affecting whether or not individuals can be properly linked, misinformation may result in a further reduction in power. Issues of confidentiality may be more difficult to address across multiple databases. For example, human identity information must be protected, but may be required to ensure valid merging of data. There is a great potential to better address complex issues of health and disease in companion animals and horses by integrating information across existing databases. The challenges outlined in this article should not preclude the ongoing pursuit of this approach.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 29%
Student > Ph. D. Student 6 21%
Student > Postgraduate 2 7%
Student > Doctoral Student 1 4%
Student > Master 1 4%
Other 3 11%
Unknown 7 25%
Readers by discipline Count As %
Medicine and Dentistry 6 21%
Agricultural and Biological Sciences 4 14%
Psychology 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Mathematics 1 4%
Other 4 14%
Unknown 10 36%
Attention Score in Context

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 26 October 2011.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from Acta Veterinaria Scandinavica
#440
of 837 outputs
Outputs of similar age
#93,393
of 126,624 outputs
Outputs of similar age from Acta Veterinaria Scandinavica
#9
of 11 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 837 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 126,624 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.