Name
Title | ||
|---|---|---|
Supporting Data Collection in Complex Scenarios with Dynamic Data Collection Processes |
Abstract | ||
|---|---|---|
Nowadays, companies have to report a large number of data sets (e.g., sustainability data) regarding their products to different legal authorities. However, in today's complex supply chains products are the outcome of the collaboration of many companies. To gather the needed data sets, companies have to employ cross-organizational and long-running data collection processes that imply great variability. To support such scenarios, we have designed a lightweight, automated approach for contextual process configuration. That approach can capture the contextual properties of the respective situations and, based on them, automatically configure a process instance accordingly, even without human involvement. Finally, we implemented our approach and started an industrial evaluation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-19270-3_4 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
Process configuration,Business process variability,Data collection,Sustainability,Supply chain | Data collection,Process configuration,Data mining,Data set,Systems engineering,Computer science,Dynamic data,Supply chain,Sustainability | Conference |
Volume | ISSN | Citations |
204 | 1865-1348 | 0 |
PageRank | References | Authors |
0.34 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gregor Grambow | 1 | 28 | 5.40 |
| Nicolas Mundbrod | 2 | 43 | 6.72 |
| Jens Kolb | 3 | 185 | 12.57 |
| Manfred Reichert | 4 | 50 | 5.12 |