Presentation
Standardizing Process-Data Exploitation by Means of a Process-Instance Metamodel
Author/s | Cancela, Antonio
Reina Quintero, Antonia María García García, Alejandro Gómez López, María Teresa |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2018 |
Deposit Date | 2022-10-31 |
Published in |
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ISBN/ISSN | 978-3-030-46632-9 1865-1348 |
Abstract | The analysis of data produced by the enterprises during pro cesses execution is key to know how these processes are working and how
they can be improved. These data may be consumed to make different
types of analysis, ... The analysis of data produced by the enterprises during pro cesses execution is key to know how these processes are working and how they can be improved. These data may be consumed to make different types of analysis, for example, data could be used as input for process dis covery, decision-making and even process querying tools. However, each type of analysis needs data in different formats because they use different techniques and tackle the problem from a different point of view. Fortu nately, if we look at the data exploitation problem from a higher level of abstraction perspective, we can realize that all the points of view share a common ground: the business process model and its instantiation are in the kernel of all of them. In this paper, we propose the use of a Busi ness Process Instance Metamodel, which serves as a common interface to make independent the applications producing business process data from those applications that consume and exploit it. A tool has been implemented as a proof of concept to facilitate the matching between data from different data sources and the metamodel. |
Funding agencies | Ministerio de Ciencia Y Tecnología (MCYT). España |
Project ID. | TIN2015-63502-C3-2-R
TIN2016-75394-R |
Citation | Cancela, A., Reina Quintero, A.M., García García, A. y Gómez López, M.T. (2018). Standardizing Process-Data Exploitation by Means of a Process-Instance Metamodel. En SIMPDA 2018: 8th International Symposium on Data-Driven Process Discovery and Analysis (52-66), Sevilla, España: Springer. |
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