Compliance validation and diagnosis of business data constraints in business processes at runtime
Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored. These data must satisfy the business compliance rules associated with the process, where business complianc...
| Authors: | ; ; |
|---|---|
| Format: | Article |
| Status: | Submitted version |
| Publication date: | 2015 |
| Country: | España |
| Institution: | Universidad de Sevilla (US) |
| Repository: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/138262 |
| Online Access: | https://hdl.handle.net/11441/138262 https://doi.org/10.1016/j.is.2014.07.007 |
| Access Level: | Open access |
| Keyword: | Business processes validation and diagnosis Business data constraints Persistence data Constraint programming |
| _version_ | 1878733080101912576 |
|---|---|
| author | Gómez López, María Teresa |
| author2 | Martínez Gasca, Rafael Pérez Álvarez, José Miguel |
| author2_role | author author |
| author_browse | Gómez López, María Teresa Martínez Gasca, Rafael Pérez Álvarez, José Miguel |
| author_facet | Gómez López, María Teresa Martínez Gasca, Rafael Pérez Álvarez, José Miguel |
| author_role | author |
| collection | idUS. Depósito de Investigación de la Universidad de Sevilla |
| description | Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored. These data must satisfy the business compliance rules associated with the process, where business compliance rules are policies or statements that govern the behaviour of a company. To improve and automate the validation and diagnosis of compliance rules based on the description of data semantics (called Business Data Constraints), we propose a framework where dataflow variables and stored data are analyzed. The validation and diagnosis process is automated using Constraint Program-ming, to permit the detection and identification of possibly unsatisfiable Business Data Constraints, even if the data involved in these constraints are not all instantiated. This implies that the potential errors can be determined in advance. Furthermore, a language to describe Business Data Constraints is proposed, for the improvement of user-oriented aspects of the business process description. This language allows a business expert to write Business Data Constraints that will be automatically validated in run-time, without the support of an information technology expert. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_4fae4e9e10bfeaab6d04bb95dffa761f |
| institution | Universidad de Sevilla (US) |
| instname_str | Universidad de Sevilla (US) |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:idus.us.es:11441/138262 |
| publishDate | 2015 |
| publishDateSort | 2015 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| reponame_str | idUS. Depósito de Investigación de la Universidad de Sevilla |
| spelling | Compliance validation and diagnosis of business data constraints in business processes at runtime Gómez López, María Teresa Martínez Gasca, Rafael Pérez Álvarez, José Miguel Business processes validation and diagnosis Business data constraints Persistence data Constraint programming Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored. These data must satisfy the business compliance rules associated with the process, where business compliance rules are policies or statements that govern the behaviour of a company. To improve and automate the validation and diagnosis of compliance rules based on the description of data semantics (called Business Data Constraints), we propose a framework where dataflow variables and stored data are analyzed. The validation and diagnosis process is automated using Constraint Program-ming, to permit the detection and identification of possibly unsatisfiable Business Data Constraints, even if the data involved in these constraints are not all instantiated. This implies that the potential errors can be determined in advance. Furthermore, a language to describe Business Data Constraints is proposed, for the improvement of user-oriented aspects of the business process description. This language allows a business expert to write Business Data Constraints that will be automatically validated in run-time, without the support of an information technology expert. Junta de Andalucía P08-TIC-04095 Ministerio de Ciencia y Tecnología TIN2009-13714 Elsevier https://hdl.handle.net/11441/138262 https://doi.org/10.1016/j.is.2014.07.007 |
| spellingShingle | Compliance validation and diagnosis of business data constraints in business processes at runtime Gómez López, María Teresa Business processes validation and diagnosis Business data constraints Persistence data Constraint programming |
| status_str | submittedVersion |
| title | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| title_full | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| title_fullStr | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| title_full_unstemmed | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| title_short | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| title_sort | Compliance validation and diagnosis of business data constraints in business processes at runtime |
| topic | Business processes validation and diagnosis Business data constraints Persistence data Constraint programming |
| topic_facet | Business processes validation and diagnosis Business data constraints Persistence data Constraint programming |
| url | https://hdl.handle.net/11441/138262 https://doi.org/10.1016/j.is.2014.07.007 |