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Mobile data collection tokmakoff

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Mobile data collection. Presentation by Andrew Tokmakoff at ESA conference workshop 1 October 2014

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Mobile data collection tokmakoff

  1. 1. 1 Collecting Data Mobile field data collection with prescribed methodologies 01/10/14, Andrew Tokmakoff
  2. 2. 2 Objectives of this talk ✤ Gain an overview of what (mobile) field data collection means and what it can offer. ✤ Understand why you would collect your field data using mobile technologies. ✤ Benefits and Challenges of mobile field data collection. ✤ Familiarise with the AusPlots solution (Field Data collection App).
  3. 3. 2 What do we mean by “mobile field data collection”?
  4. 4. 2 ‘Traditional’ field data collection ✤Out in the field, pen and paper. ✤ Data entry back in the office
  5. 5. 2 Mobile field data collection ✤On-site electronic recording of collected data. ✤ Data curation (if necessary) back in the office
  6. 6. 2 Mobile field data collection: Benefits ✤ Less data-entry drudgery back at the office (but more in the field?) ✤ Less chance of transcription errors (handwriting legibility) ✤ Collecting highly consistent data (which is easier to curate and to analyse)
  7. 7. 2 Mobile field data collection: Costs ✤ Potential for slower collection of data (slow and unintuitive User Interfaces, bugs). ✤ Screen visibility in high sun and robustness of hardware in harsh conditions (consumer vs ruggedised). ✤ Time and effort required to select a solution and to customise it to own needs.
  8. 8. 2 The ‘R’ word… ✤ So, what are your “requirements”? Scoping is key. ✤ Cost-benefit trade-off
  9. 9. 2 Considerations ✤ Complexity of collected data ✤ availability of “commercial” off-the-shelf (COTS) solutions vs custom ✤ relations between data items and associated integrity of data
  10. 10. 2 Considerations ✤ Data collection turnaround times ✤ are there data consumers waiting on you?
  11. 11. 2 Considerations ✤ Importance of data ”cleanliness” ✤ i.e. costs of “clean” data collection vs subsequent curation and cleansing.
  12. 12. 2 Considerations ✤ Do you have external tools or other software systems that expect your data in a certain format? ✤ i.e. analysis tools, data warehouses, archives
  13. 13. 2 Considerations ✤ Where is your data going to go? Will it be shared/published/ backed up?
  14. 14. 2 Typical scenarios ! ✤ Pen and Paper with laptop (spreadsheet or database) ✤ Off-the shelf App on mobile device ✤ Custom App on mobile device Decision time..!
  15. 15. 2 The AusPlots Approach
  16. 16. System Architecture 3 cron Internet Data Upload Apach e/PHP Field App Web-based Admin Interface (Cloud) SWARM Server
  17. 17. 5 Field App: what is it, and who is it for? ✤ It’s an (Android) mobile application that electronically collects field data according to the AusPlots data collection specification. ✤ Who wants it? Anyone (i.e. ecological scientists and assistants) who: ✤ collects, manages and shares AusPlots field data ✤ wants to minimise data entry errors and transcription effort ✤ wants the data to be automatically archived for easy use later on.
  18. 18. Field App: Plot Creation 5
  19. 19. Field App: Site Description 6
  20. 20. Field App: Veg. Vouchering 7
  21. 21. Field App: Point Intercept 8
  22. 22. Field App: Basal Wedge 9
  23. 23. Field App: Structural Summary 10
  24. 24. Field App: Plot Upload 11
  25. 25. Data Management: Curation 15 Field App Web-based Admin Interface cron REST/ JSON Apache /PHP (Cloud) SWARM Server ✤ Apache/PHP web “site” provides a User Interface for data curation. ✤ Allows “cleaning” of data and entry of new items such as herbarium determinations.
  26. 26. Publishing: 3rd parties ✤ Soils 2 Satellites offers visualisation ✤ (e.g. for land managers, consultants) ✤ Aekos offers raw data access, data enrichment and search ✤ (e.g. for ecological scientists) 16 Field App cron REST/ JSON (Cloud) SWARM Server
  27. 27. 2 A demo of the App
  28. 28. 2 Benefits and Challenges ✤ Benefits: ✤ Speed of data availability ✤ Integrity of data ✤ Challenges: ✤ getting the UI right; resistance when it is slower than “recording audio with subsequent data entry”. ✤ dealing with legacy data at the same time as introducing new tools.
  29. 29. 2 Looking ahead… ✤New Woodlands and Forests modules w/ protocols ✤ veg condition and Fauna likely to be first ✤ iOS support
  30. 30. 2 General Recommendations ✤ Try to think ahead, but avoid gold-plating and over-engineering. ✤ Take some time to design your schema / tables. ✤ Add some mechanisms to “enforce” your data cleanliness. ✤ Assume you will need to iterate.
  31. 31. Summary ✤ Have a good think about your genuine requirements and your budget…!! ✤ The AusPlots Field Data Collection App has been used to collect field data from over 250 (of 450) plots. ✤ It has been developed iteratively, based upon experience from field use. ✤ It produces “cleaner” data than existing techniques. ✤ Data is uploaded to a server and is curated there. ✤ A “demo version” of the App is being developed for general availability 17
  32. 32. Any Questions? AusPlots and ATN Technical Lead andrew.tokmakoff@adelaide.edu.au 18 Andrew Tokmakoff

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