4th ComplexWorld Workshop. Stockholm, Thursday 28th of November 2013
Classical (key performance indicators) and non-classical metrics.
This year, as part of its Knowledge Development activities, the WP_E ComplexWorld Network is organizing a number of workshops on topics related to “Complexity and ATM”. The main objective is to advance the contents of the ComplexWorld Position Paper (which you can find in the ComplexWorld Wiki).
We now announce the fifth workshop (WS5), called “Complex Metrics in ATM”, which will take place in Stockholm, on Thursday 28 November 2013, from 14:00 to 17:30 h. The workshop is run alongside the SESAR Innovation Days Conference, taking place during the last day of the conference, in order to minimize additional travel and allow those of you already participating in SID to attend.
The objective of these Workshops is twofold:
- To advance the knowledge development carried out by the ComplexWorld Network, and;
- To involve WP-E Projects and PhDs in the maintenance of the state-of-the-art on “Complex Metrics in ATM”.
We use the term ‘classical’ metrics to denote those that are pre-defined (such as average aircraft delay), are univariate (derived from one variable in the data), and do not draw on complexity science techniques. Some of these types of metric are already commonly in use (such as, indeed, average aircraft delay), whilst others are not (such as average passenger delay) – and, arguably, thus conspicuous by their absence.
‘Non-classical’ metrics are defined to include both (non-complexity) ‘derived’ metrics, which are in contrast to the classical metrics in that they are not (fully) pre-defined, but are derived from the data iteratively and are typically multivariate, and those drawn from complexity science. An example of a derived metric is a factor obtained as the result of factor analysis An example of a (simple) complexity metric is the degree of a node (e.g. number of connections from and to an airport). With regard to the metrics, the workshop will focus on the non-classical metrics set and its subset, complexity metrics. Data mining techniques may be applied not only to generate non-classical metrics, but also in topology characterization, such as identifying complex network communities (groups of densely connected nodes, sharing only few connections with nodes outside their group). These techniques are not needed to calculate classical metrics.
We consider that this topic will be of special interest for the projects and PhD students listed below, but if you think that the topic is interesting for your field of research or linked to your expertise, we welcome your participation in our workshop. The WP-E Projects which might be targeted by WS5 are: e.g. CASSIOPEIA, ComplexityCosts, ELSA, NEWO, POEM, TREE, and the PhDs are those relating to complex metrics
If you are interested in attending or would like to know more, please contact
Prof. Hartmut Helmke, DLR (Hartmut.Helmke@dlr.de).
Send us your inputs for the workshop. What should be discussed? Which items should be fixed in the state-of-the-art on “Complex Metrics in ATM”?.
We will update this website with your inputs which will serve to collaboratively schedule the agenda.