ODK useful for literature overviews?

I am doing systematic literatursearch as a nursing scientist. And beside of that I am a software developer.
But my colleagues are not. So I have to choose tools that fit to my "nerdy" needs and to the easy-to-use needs of my colleagues.

The data of my researches are bit and wide tables with informations I extract from publications (e.g. 50 publications in one review). It is not data like in a quantitative meta analysis. Most of them is text, about characteristics about the intervention, population of each study. This is only one table and most of my colleagues do this with Excel.

I want to present the data in some tables (views) in a PDF file and Excle(-like) file. I want to analyse it with R. Maybe I want to transform or do some more complexe stuff with it while accessing it with a Python-Script (e.g. using sqlalchemy package).

Some fields have a n:m connection (in relational database speech). Asume a study which was done in more then one country. In a rational database I would create a n:m relation like that.


  • id
  • title


  • id
  • name


  • id
  • country_id
  • publication_id

I think there won't be more complex data like this.

The question is if ODK can help me (and my colleagues!) to handle this without wasting to much time and without doing to much manualy?
The "Download" page of ODK is big. On which components should I look here?

btw: Does ODK use any cloud services or can I use it 100% local (or with setting up my own server)?

Although ODK is awesome, it's designed primarily for mobile data collection. Regarding the relational data you're discussing, it sounds like you're talking about something that can already be managed in statistical software. For instance, I work in STATA, and with a database where an observation equals a study, you can collapse down to count or otherwise analyze data on different levels. You can also restructure the data from "long" to "wide" formats. I think R has equivalent commands.

You are right this could be done in a statistical package. I can do it. But not my colleagues. :wink: This is just to complex for them.

1 Like