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1 
Collecting Data 
Mobile field data collection with prescribed methodologies 
01/10/14, Andrew Tokmakoff
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).
2 
What do we mean by 
“mobile field data 
collection”?
2 
‘Traditional’ field data collection 
✤Out in the field, pen and paper. 
✤ Data entry back in the office
2 
Mobile field data collection 
✤On-site electronic recording of collected data. 
✤ Data curation (if necessary) back in the office
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)
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.
2 
The ‘R’ word… 
✤ So, what are your “requirements”? Scoping is key. 
✤ Cost-benefit trade-off
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
2 
Considerations 
✤ Data collection turnaround times 
✤ are there data consumers waiting on you?
2 
Considerations 
✤ Importance of data ”cleanliness” 
✤ i.e. costs of “clean” data collection vs 
subsequent curation and cleansing.
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
2 
Considerations 
✤ Where is your data going to go? Will it be shared/published/ 
backed up?
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..!
2 
The AusPlots Approach
System 
Architecture 
3 
cron 
Internet 
Data 
Upload 
Apach 
e/PHP 
Field App 
Web-based Admin Interface 
(Cloud) SWARM Server
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.
Field App: Plot Creation 
5
Field App: Site Description 
6
Field App: Veg. Vouchering 
7
Field App: Point Intercept 
8
Field App: Basal Wedge 
9
Field App: Structural Summary 
10
Field App: Plot Upload 
11
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.
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
2 
A demo of the App
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.
2 
Looking ahead… 
✤New Woodlands and Forests modules w/ protocols 
✤ veg condition and Fauna likely to be first 
✤ iOS support
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.
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
Any Questions? 
AusPlots and ATN Technical Lead 
andrew.tokmakoff@adelaide.edu.au 
18 
Andrew Tokmakoff

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Mobile data collection tokmakoff

  • 1. 1 Collecting Data Mobile field data collection with prescribed methodologies 01/10/14, Andrew Tokmakoff
  • 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. 2 What do we mean by “mobile field data collection”?
  • 4. 2 ‘Traditional’ field data collection ✤Out in the field, pen and paper. ✤ Data entry back in the office
  • 5. 2 Mobile field data collection ✤On-site electronic recording of collected data. ✤ Data curation (if necessary) back in the office
  • 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. 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. 2 The ‘R’ word… ✤ So, what are your “requirements”? Scoping is key. ✤ Cost-benefit trade-off
  • 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. 2 Considerations ✤ Data collection turnaround times ✤ are there data consumers waiting on you?
  • 11. 2 Considerations ✤ Importance of data ”cleanliness” ✤ i.e. costs of “clean” data collection vs subsequent curation and cleansing.
  • 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. 2 Considerations ✤ Where is your data going to go? Will it be shared/published/ backed up?
  • 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. 2 The AusPlots Approach
  • 16. System Architecture 3 cron Internet Data Upload Apach e/PHP Field App Web-based Admin Interface (Cloud) SWARM Server
  • 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. Field App: Plot Creation 5
  • 19. Field App: Site Description 6
  • 20. Field App: Veg. Vouchering 7
  • 21. Field App: Point Intercept 8
  • 22. Field App: Basal Wedge 9
  • 23. Field App: Structural Summary 10
  • 24. Field App: Plot Upload 11
  • 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. 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. 2 A demo of the App
  • 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. 2 Looking ahead… ✤New Woodlands and Forests modules w/ protocols ✤ veg condition and Fauna likely to be first ✤ iOS support
  • 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. 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. Any Questions? AusPlots and ATN Technical Lead andrew.tokmakoff@adelaide.edu.au 18 Andrew Tokmakoff