EnviroSensing Monthly telecons

From Earth Science Information Partners (ESIP)
Revision as of 16:04, September 26, 2014 by Donhenshaw (talk | contribs)

back to EnviroSensing Cluster main page

Telecons on the fourth Tuesday of every month at 4:00pm ET. Click on 'join'

Next telecon October 28, 2014, 4:00 PM EDT, Wade Sheldon: GCE Matlab data toolbox

November 25, 2014, 4:00 PM EDT. Jordan Read will introduce the R package SensorQC

Notes from past telecons

9/23/2014

  • Fox Peterson (Andrews LTER) reported on QA/QC methods they are applying to historic climate records (~13 million data points for each of 6 sites).

The challenge was that most automated approaches still produced too many flagged data that needed to be manually checked. Multiple statistical methods were tested based on long-term historical data. The method they selected was to use a moving window of data from the same hour over 30 days and test for 4 standard deviations in that window; E.g., use all data for 1 pm for days 30 - 60 of the year, compute four standard deviations, and set the range for the midpoint day (45) at the 1pm hour to that range.

  • Josh Cole reported on his system, which is in development and he will be able to share scripts with the group.
  • Brief discussion of displaying results using web tools.
  • Great Basin site discussed the variability in their data, which "has no normal"-- how could we perform qa/qc based on statistics and ranges in this case?
  • Discussion of bringing Wade Sheldon to call next time / usefulness of the toolbox for data managers
  • Discussion of using Pandas package- does anyone have experience, can we get them on?
  • Discussion of the trade off between large data stores, computational strength, and power. Good solutions?
  • ESIP email had some student opportunities which may be of interest
  • Overall, it was considered helpful if people were willing to share scripts. Discussion of a GIT repository for the group, or possibly just use the Wiki.


8/26/2014

Suggestions for future discussion topics

  • Citizen Science contributions to environmental monitoring
  • 'open' sensors - non-commercial sensors made in-house, technology, use, best practices
  • Latest sensor technologies
  • Efficient data processing approaches
  • Online data visualizations
  • New collaborations to develop new algorithms for better data processing
  • Sensor system management tools (communicating field events and associating them with data)