I am currently using the great ODK app in my Phd project for a large field study on water and hygiene in Chad.
However there is one issue left for me to follow up on, especially since my group is currently or will soon be starting similar projects and we are thus likely to run into the same problem again. As I work in a rather weak infrastructural and connection-lacking environment, I have been searching for a way to gather and aggregate the data offline on my personal computer. Our enumerators brought back the devices every night for data back up on hard disk anyways, so I figured going offline with data aggregation for review as well as analysis later on would be the easiest way.
I have searched the net but only found the following two solutions below. (And wondered whether not more people have this issue?)
One would be, as I read, to use the ODK aggregate tool working offline by setting up your own server to run locally on the laptop. I might be wrong on this, but I found the descriptions rather complicated and honestly have not gone all the way trying it out. I only know that one of my colleagues currently facing the problem gave up on this. And as we do not rely on any other of the functions aggregate seems to offer except the aggregation part itself, this seems to me breaking a butterfly on a wheel.
I have ended up using the KoBo PostProcessor, which – after some night hours of trial and error with different parts of the toolbox – worked for me. There are some issues though as well with this program. First of all, the promised function of pulling the data directly from the devices did not work for me, neither from internal storage nor from the supplementary SD card. Secondly, in order to aggregate, I have to click the “Aggregate”-button for each file-within-folder individually, which – for the upcoming several thousand Ns – is a pain in the …. In conclusion my impression of the KoBo tool was not a very stable and elaborated one. In the end it worked out for my needs, but I don’t see this routine working well for larger projects.
Also, currently I have some trouble using KoBo the way I did before due to security settings in my browser (firefox) that doesn't allow running the aggregation script anymore....
Are there any other solutions for this task you know of?
I think ODK Briefcase (http://opendatakit.org/use/briefcase/) is your
best bet. It can pull the data from your device (over USB) and store
it on your computer. You can then export it to CSV or even push it up
from your computer to an Aggregate server.
Another option is the ODK Aggregate VM
(http://gum.co/odk-aggregate-vm) which makes it easier for you to
install ODK Aggregate. It's probably more heavy weight that you need,
so I'd recommend you try Briefcase first.
Yaw
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I am currently using the great ODK app in my Phd project for a large field study on water and hygiene in Chad.
However there is one issue left for me to follow up on, especially since my group is currently or will soon be starting similar projects and we are thus likely to run into the same problem again. As I work in a rather weak infrastructural and connection-lacking environment, I have been searching for a way to gather and aggregate the data offline on my personal computer. Our enumerators brought back the devices every night for data back up on hard disk anyways, so I figured going offline with data aggregation for review as well as analysis later on would be the easiest way.
I have searched the net but only found the following two solutions below. (And wondered whether not more people have this issue?)
One would be, as I read, to use the ODK aggregate tool working offline by setting up your own server to run locally on the laptop. I might be wrong on this, but I found the descriptions rather complicated and honestly have not gone all the way trying it out. I only know that one of my colleagues currently facing the problem gave up on this. And as we do not rely on any other of the functions aggregate seems to offer except the aggregation part itself, this seems to me breaking a butterfly on a wheel.
I have ended up using the KoBo PostProcessor, which - after some night hours of trial and error with different parts of the toolbox - worked for me. There are some issues though as well with this program. First of all, the promised function of pulling the data directly from the devices did not work for me, neither from internal storage nor from the supplementary SD card. Secondly, in order to aggregate, I have to click the "Aggregate"-button for each file-within-folder individually, which - for the upcoming several thousand Ns - is a pain in the .... In conclusion my impression of the KoBo tool was not a very stable and elaborated one. In the end it worked out for my needs, but I don't see this routine working well for larger projects.
Also, currently I have some trouble using KoBo the way I did before due to security settings in my browser (firefox) that doesn't allow running the aggregation script anymore....
Are there any other solutions for this task you know of?
thanks for the reply. I now have a standalone version of Briefcase running which works for data aggregation to .csv, as well as the KoboPostprocessor option of doing this. The outputs slightly differ in appearance however - especially repeated groups seem to be processed differently. I'll see how the combination will work out as soon as more data is coming in.
I would like to add two specific pieces of information for all those who would like to use Briefcase for similar tasks:
The folder substructure in the Briefcase Storage Location needs to be very specific so that it matches the internal needs of the program. This is especially important when data is copied manually from the phone/tablet and not via the "Pull" function in Briefcase (which can also have issues when the device's storage is not recognized by Briefcase). This has been neatly described here: http://racooncode.com/2011/11/09/converting-odk-xml-data-to-csv. The strucure must resemble the internal ODK folder structure on the Android system.
The ODK Briefcase description manual is lacking a detailed guide on how to use the aggregation function. Its basic functioning is however understandable by looking at the program GUI itself. But for further issues (e.g. see above the processing of repeated groups) there seems to be no description available.
You shouldn't manually copy the files into the Briefcase storage
location. Copy the /odk folder to the desktop of your computer, then
use Briefcase to import using the "Custom path to ODK directory"
option. That import will automatically place the files in the right
place in the Briefcase storage location.
As far as guides, perhaps that is something you or someone else can
contribute to the community? We'd be glad to link it to the other
guides at http://opendatakit.org/help/training-guides/.
Thanks,
Yaw
···
--
Need ODK services? http://nafundi.com provides form design, server
setup, professional support, and software development for ODK.
thanks for the reply. I now have a standalone version of Briefcase running which works for data aggregation to .csv, as well as the KoboPostprocessor option of doing this. The outputs slightly differ in appearance however - especially repeated groups seem to be processed differently. I'll see how the combination will work out as soon as more data is coming in.
I would like to add two specific pieces of information for all those who would like to use Briefcase for similar tasks:
The folder substructure in the Briefcase Storage Location needs to be very specific so that it matches the internal needs of the program. This is especially important when data is copied manually from the phone/tablet and not via the "Pull" function in Briefcase (which can also have issues when the device's storage is not recognized by Briefcase). This has been neatly described here: http://racooncode.com/2011/11/09/converting-odk-xml-data-to-csv. The strucure must resemble the internal ODK folder structure on the Android system.
The ODK Briefcase description manual is lacking a detailed guide on how to use the aggregation function. Its basic functioning is however understandable by looking at the program GUI itself. But for further issues (e.g. see above the processing of repeated groups) there seems to be no description available.