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h2. Metrics Ccatalogue

{info:title=Note}
We are currently in the process of merging the initial _evaluations_ metrics catalogue into the attribute/measure catalogue being developed in the PW work package. When this has happened, all experiments should only use metrics from the latter mentioned catalogue.
Also, preferable this page will describe how to navigate the catalogue, so it will be easy to find the proper metrics and more time can be spent on the experiments.
{info}

h4. Picking metrics
When picking metrics for an evaluation, run through the catalogue and pick any already defined, or enter a new metric when needed.

The attribute/measure catalogue developed in PW can be found here [Measures |http://ifs.tuwien.ac.at/dp/vocabulary/quality/measures]
Also, an equivalent attribute/measure source can be found in this google doc [Measures by google doc |https://docs.google.com/spreadsheet/ccc?key=0An_F2fZCFRRtdGZ6NFg0eFI3b3NIdktMSzBtWmhKUHc&pli=1#gid=0]
h4. This is the previously used evaluation metrics

To unify metrics across all evaluations all metrics should be registered in this Metrics Catalogue. So - when picking metrics for an evaluation run through the catalogue and pick any already defined or enter a new metric when needed.

{code}Use CamelCase notation for metric names - e.g. NumberOfObjectsPerHour{code}

|| Metric \\ || PW catalogue \\ URI || Datatype \\ || Description \\ || Example \\ || Comments \\ ||
URI || Datatype \\ || Description \\ || Example \\ || Comments \\ ||
| NumberOfObjectsPerHour | | integer | Number of objects that can be processed per hour \\ | 250 \\ | Could be used both for component evaluations on a single machine and on entire platform setups \\ |
| IdentificationCorrectnessInPercent | | integer \\ | Defining a statistical measure for binary evaluations - [see detailed specification below|#Metricscatalogue-fmeasure] | 85 % \\ | Between 0 and 100 \\ |



This is one suggested way, which is nicely applicable, if we test for binary correctness of calculations, i.e. it is applicable for characterisation and QA.