In January 2011, a formal experiment was conducted which aimed to clear some questions in the field of personal information management (PIM), information re-finding, and information architecture. This repository holds relevant data to verify or extend this experiment.
For this purpose, the testing framework tagstore (http://tagstore.org) was used to compare storing files (images, graphics and documents) within the folder hierarchy using Microsoft Windows Explorer and tagstore.
The tagstore framework supports file management by applying tags. Those tags are being used to (automatically) generate navigation hierarchies, called TagTrees.
This repository contains anonymous data from the experiment in order to check, extend, or re-evaluate the experiment.
This is Open Data.
This is Open Science.
In April 2011, we basically repeated the January-experiment. The April experiment has less technical logs, a two week pause between filing and re-finding, more test persons, more test items, more detailed questionnaires: https://github.com/novoid/2011-04-tagstore-formal-experiment
The experiment was conducted by a group of Karl Voit (Graz University of Technology) and took place in Graz, Austria. Therefore, the language of the test persons was German. All data which test persons were confronted with is in German. Derived data and supplementary things such as evaluation scripts are in English though.
Several related white papers are linked on the tagstore homepage.
https://github.com/novoid/2011-01-tagstore-formal-experiment is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
For now, all relevant experiment data is online. If something is not online (like for example the TP videos), a README.org explains further things or links to an alternative hosting place.
Currently, the detailed results are being extracted. The raw results are somewhat irritating due to several things like bugs in software.
Here is the list of things which will be published here in future:
Python-parser are reading the transcript files and generate a ASCII and CSV summary per transcript file. Those parsers will be published too.
The raw summary CSV files (all TPs) are committed already. The spreadsheets containing the derived diagrams will be published soon.
A report containing the most important results will be published here.
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