Difference between revisions of "Sampling with GPS-enabled smartphone and DII"

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Between 2015 and 2017 a team of researchers involved in the projects [http://www.mod-co.net/wiki/Main_Page MOD-CO] and [https://www.gfbio.org/ GFBio] worked on a best practice workflow for field ecologists. The aim was to enable researchers for effective sampling environmental vouchers with digital documentation of essential parameters already during the field campaign. The workflow established together with co-worekers from Kenya and Algeria included the sampling with GPS-enabled smartphone and the set up of a generic, effective procedure which is basically independent from any data management solution or specific collection management system. The DWB team was involved in the design and implementation of the new data processing tool [[DiversityImageInspector]] (DII) which finally is generating CSV tables.  
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Between 2015 and 2017 a team of researchers involved in the projects [http://www.mod-co.net/wiki/Main_Page MOD-CO] and [https://www.gfbio.org/ GFBio] worked on '''a best practice workflow for field ecologists'''. The aim was to enable researchers for effective sampling environmental vouchers with digital documentation of essential parameters already during the field campaign. The workflow established together with co-workers from Kenya and Algeria included the sampling with GPS-enabled smartphone and the set up of a generic, effective procedure which is basically independent from any data management solution or specific collection management system. The DWB team was involved in the design and implementation of the new data processing tool [[DiversityImageInspector]] '''(DII)''' which finally is generating CSV tables.  
  
 
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The workflow described in [https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113 Triebel et al. (2018)] has 5 steps. The elements of step 1 to 4 (without data management in DWB databases) are visualised by [https://academic.oup.com/view-large/figure/108104585/bax096f1.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 1], [https://academic.oup.com/view-large/figure/108104588/bax096f2.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 2], [https://academic.oup.com/view-large/figure/108104595/bax096f3.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 3] and [https://academic.oup.com/view-large/figure/108104599/bax096f4.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 4].
  
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*Instructions to extend the work for step 2 of the workflow described by Triebel et al. 2018
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The pages linked here give '''supplementary information''' on
**[[Procedure for preparing UUID-QR-codes for labelling sampling containers| the description of a procedure for preparing UUID-QR-codes for labelling sampling containers]]
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** hints how to manually prepare UUID-QR-coded paper envelopes
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** hints concerning carrier types and their subsequent use of UUID-QR-coding of samples during analysis processes
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*[[Procedure for preparing UUID-QR-codes for labelling sampling containers|How to prepare UUID-QR-codes for labelling sampling containers]]
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*[[How to prepare UUID-QR-coded paper envelopes]]
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*[[How to select carrier types and use UUID-QR-coding of samples during analysis processes]]
  
*Detailed information on Step 4 of the workflow include
 
 
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For photo documentation of samples in the field and subsequent processing using [[DiversityImageInspector]] see [https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113. Triebel et al. (2018)].
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Sample datasets from a research project in Africa ([http://www.kws.go.ke/content/ruma-national-park Ruma National Park]) with CSV table are deposited under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector '''(to be improuved)'''. This file (with import schema applied) is appropriate to be imported in [[DiversityCollection]], as visualised by [https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113 Triebel et al. (2018)], [https://academic.oup.com/view-large/figure/108104602/bax096f5.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 5] and [https://academic.oup.com/view-large/figure/108104603/bax096f6.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 6].
  
By use of GPS-enabled smartphone or a digital camera, images may be taken for full documentation of the collection event for one sample in the field.
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[https://academic.oup.com/view-large/figure/108104588/bax096f2.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Triebel et al. (2018), Fig. 2]
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Reference:
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Images may be further processed using DiversityImageInspector. It concerns the interpretation and extraction of the QR-code information from the image content, as well as the extraction of the tag information from the Exif header of the images
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*Triebel, D., Reichert, W., Bosert, S., Feulner, M., Osieko Okach, D., Slimani, A. & Rambold, G. 2018. A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing. – Database, 2018 (Article ID bax096), 1–10. ([https://doi.org/10.1093/database/bax096 doi.org/10.1093/database/bax096]), see https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113.
  
[https://academic.oup.com/view-large/figure/108104595/bax096f3.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Triebel et al. (2018), Fig. 3]
 
 
The DiversityImageInspector is combining both information for export as a CSV-formatted document, which may be imported into any RDB system with corresponding model elements.
 
 
[https://academic.oup.com/view-large/figure/108104599/bax096f4.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Triebel et al. (2018), Fig. 4]
 
 
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**Sample datasets with csv table are deposited under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector  (to be improuved). This file (with import schema applied)is appropriate to be imported in DC.
 
 
*Figures 1 to Figures 8 describes a use case in Kenya, Ruma
 
  
 
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Reference:
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'''Back to [[Training materials ]]'''
 
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*Triebel, D., Reichert, W., Bosert, S., Feulner, M., Osieko Okach, D., Slimani, A. & Rambold, G. 2018. A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing. – Database, 2018 (Article ID bax096), 1–10. ([https://doi.org/10.1093/database/bax096 doi.org/10.1093/database/bax096]), see https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113.
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Latest revision as of 10:57, 23 January 2018

Between 2015 and 2017 a team of researchers involved in the projects MOD-CO and GFBio worked on a best practice workflow for field ecologists. The aim was to enable researchers for effective sampling environmental vouchers with digital documentation of essential parameters already during the field campaign. The workflow established together with co-workers from Kenya and Algeria included the sampling with GPS-enabled smartphone and the set up of a generic, effective procedure which is basically independent from any data management solution or specific collection management system. The DWB team was involved in the design and implementation of the new data processing tool DiversityImageInspector (DII) which finally is generating CSV tables.


The workflow described in Triebel et al. (2018) has 5 steps. The elements of step 1 to 4 (without data management in DWB databases) are visualised by Fig. 1, Fig. 2, Fig. 3 and Fig. 4.


The pages linked here give supplementary information on


Sample datasets from a research project in Africa (Ruma National Park) with CSV table are deposited under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector (to be improuved). This file (with import schema applied) is appropriate to be imported in DiversityCollection, as visualised by Triebel et al. (2018), Fig. 5 and Fig. 6.


Reference:




Back to Training materials