This project has received funding from the European Union's 7th Framework Programme for Research, Technological Development and Demonstration under Grant Agreement (GA) N° #607798

Giving you inspiration,
examples and guidance
during the preparation phase


What this tool
is for

The DRIVER+ knowledge base, in its current version, contains the results of a systematic literature review (SLR) of trial-like events in the crisis management domain from the past decade.

The SLR approach is a means to reduce the bias of study selection, data extraction and presentation as well as to ensure high quality, because it is reproducible due to the systematic and well documented procedure. The knowledge of the relevant identified sources was collected in codebooks. These codebooks contain ten different categories, that were filled based on the analysis of the literature: objective, research question, planning & deviation, research method, metrics & KPIs, data collection plan, data analysis, ethical procedures, results, methodological lessons learnt. By re-arranging the knowledge in this systematic way, a database was created that can be searched by using a keyword-search. The aim is to support anyone that is interested in conducting a trial by showing the state-of-the-art within those categories, that are relevant within the preparation phase. As each of the journal articles have been given an ID, they could be fed into a database that is searchable by keyword search in two ways:

Step 1: Horizontal search - search for every codebook that has information on serious games in the metrics & KPI in the same way as explained before for the research method. Results will be in the same attribute - in this example now the metrics & KPI attribute (highlighted with yellow boxes). These results could be depicted, for example, in a list giving the ID and the info about metrics.

Step 2: Vertical search - look again at the whole codebook for one ID, the whole tuple. The idea is to enable the possibility to discover more relevant information as depicted here for a specific ID, and maybe even motivate the user to go deeper and read the whole paper and its underlying research.

So please go to the TGT and try it out! You will see that it will inspire you!