Difference between revisions of "Cargo2000 DataSet"

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== Additional info ==
 
== Additional info ==
  
Link to papers or technical reports that could be useful to understand and use the artifact
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The aforementioned papers provide further insights into the data set.
  
 
== Related case study ==
 
== Related case study ==
  
In case your artifact is directly related to one or more the case studies included in this repository, please put here a link to these case studies. For instance, if the artifact implements the scenario described in the "Automotive Case Study" then add a link to the page http://scube-casestudies.ws.dei.polimi.it/index.php/Automotive_Case_Study
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Revision as of 15:40, 11 December 2013

This data set comprises real-world services monitoring data. In consists of tracking and tracing events of transports and logistics processes. Data has been pulled from a forwarding company’s Cargo 2000 system for a period of five months. From those Cargo 2000 messages, we reconstructed execution traces of 3,942 actual business process instances, comprising 7,932 transport legs and 56,082 service invocations.

Description

Brief description of the artifact and the goal of the artifact

Basic technology

Data

How to install

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How to use

When using the case study data set in your research, please cite one of the following paper to acknowledge its use:

A. Metzger, R. Franklin, and Y. Engel, “ Predictive monitoring of heterogeneous service-oriented business networks: The transport and logistics case,” in Service Research and Innovation Institute Global Conference (SRII 2012), ser. Conference Publishing Service (CPS), R. Badinelli, F. Bodendorf, S. Towers, S. Singhal, and M. Gupta, Eds. IEEE Computer Society, 2012.

Z. Feldmann, F. Fournier, R. Franklin, and A. Metzger, “Industry article: Proactive event processing in action: A case study on the proactive management of transport processes,” in Proceedings of the Seventh ACM International Conference on Distributed Event-Based Systems, DEBS 2013, Arlington, Texas, USA, S. Chakravarthy, S. Urban, P. Pietzuch, E. Rundensteiner, and S. Dietrich, Eds. ACM, 2013.

Download

You can download the data set and the description of the data in various formats from here

Additional info

The aforementioned papers provide further insights into the data set.

Related case study

N/A