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Challenges with secondary use of multi-source water-quality data in the United States

Overview of attention for article published in Water Research, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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9 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

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24 Dimensions

Readers on

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69 Mendeley
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Title
Challenges with secondary use of multi-source water-quality data in the United States
Published in
Water Research, March 2017
DOI 10.1016/j.watres.2016.12.024
Pubmed ID
Authors

Lori A. Sprague, Gretchen P. Oelsner, Denise M. Argue

Abstract

Combining water-quality data from multiple sources can help counterbalance diminishing resources for stream monitoring in the United States and lead to important regional and national insights that would not otherwise be possible. Individual monitoring organizations understand their own data very well, but issues can arise when their data are combined with data from other organizations that have used different methods for reporting the same common metadata elements. Such use of multi-source data is termed "secondary use"-the use of data beyond the original intent determined by the organization that collected the data. In this study, we surveyed more than 25 million nutrient records collected by 488 organizations in the United States since 1899 to identify major inconsistencies in metadata elements that limit the secondary use of multi-source data. Nearly 14.5 million of these records had missing or ambiguous information for one or more key metadata elements, including (in decreasing order of records affected) sample fraction, chemical form, parameter name, units of measurement, precise numerical value, and remark codes. As a result, metadata harmonization to make secondary use of these multi-source data will be time consuming, expensive, and inexact. Different data users may make different assumptions about the same ambiguous data, potentially resulting in different conclusions about important environmental issues. The value of these ambiguous data is estimated at $US12 billion, a substantial collective investment by water-resource organizations in the United States. By comparison, the value of unambiguous data is estimated at $US8.2 billion. The ambiguous data could be preserved for uses beyond the original intent by developing and implementing standardized metadata practices for future and legacy water-quality data throughout the United States.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 68 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 25%
Student > Ph. D. Student 12 17%
Student > Doctoral Student 8 12%
Student > Master 8 12%
Student > Postgraduate 5 7%
Other 11 16%
Unknown 8 12%
Readers by discipline Count As %
Environmental Science 20 29%
Engineering 13 19%
Earth and Planetary Sciences 6 9%
Agricultural and Biological Sciences 6 9%
Computer Science 4 6%
Other 7 10%
Unknown 13 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 11 December 2019.
All research outputs
#2,500,229
of 15,211,297 outputs
Outputs from Water Research
#640
of 7,504 outputs
Outputs of similar age
#77,881
of 381,277 outputs
Outputs of similar age from Water Research
#13
of 110 outputs
Altmetric has tracked 15,211,297 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,504 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 91% 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 381,277 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.