Organisational Ontology Framework for Semantic Business Process Management

Filipowska, Agata; Hepp, Martin; Kaczmarek, Monika; Marković, Ivan

doi:10.1007/978-3-642-01190-0_1

Cited by 26 publications

(12 citation statements)

References 7 publications

(15 reference statements)

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“…Therefore, in order to ensure the expected precision of the returned results, it requires ontologies which are based on compatible paradigm and have a compatible degree of details [24] (Req. Therefore, in order to ensure the expected precision of the returned results, it requires ontologies which are based on compatible paradigm and have a compatible degree of details [24] (Req.…”

Section: Requirementsmentioning

confidence: 99%

Formal Ontologies Meet Industry

Cuel¹,

Young²

2015

Lecture Notes in Business Information Processing

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Abstract. Semantic integration remains a challenge, but it is particularly problematic in areas such as e-commerce, where ontologies are either nonexistent or have lightweight axiomatizations. In this paper we present a case study that examines how two weak ontologies can be mapped together in the e-commerce setting. We also examine the role that upper-level interlingua ontologies can play in the development of ontology mappings.

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Section: Requirementsmentioning

confidence: 99%

Formal Ontologies Meet Industry

Cuel¹,

Young²

2015

Lecture Notes in Business Information Processing

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“…For that, an ontological approach [20,11] is combined with Semantic Web Services (SWS) and BPM. As in the Process Mining case, SBPM and Business Network Management are complementing approaches with combinable technology stacks.…”

Section: Related Workmentioning

confidence: 99%

From network mining to large scale business networks

Ritter

2012

Proceedings of the 21st International Conference on World Wide Web

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The vision of Large Scale Network Analysis (LSNA) states on large amounts of network data, which are produced by social media applications like Facebook, Twitter, and the competitive domain of biological networks as well as their needs for network data extraction and analysis. That raises data management challenges which are addressed by biological, data mining and linked (web) data management communities. So far, mainly these domains were considered when identifying research topics and measuring approaches and progress. We argue that an important domain, the Business Network Management (BNM), representing business and (technical) integration data, implicitely linked and available in enterprises, has been neglected. Not only do enterprises need visibilities into their business networks, they need ad-hoc analysis capabilities on them.In this paper, we introduce BNM as domain, which comes with large scale network data. We discuss how linked business data can be made explicit by what we called Network Mining (NM) from dynamic, heterogeneous enterprise environments to combine it to a (cross-) enterprise linked business data network and state on its different facets w.r.t large network analysis and highlight challenges and opportunities.

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“…For that, an ontological approach [7,6] is combined with Semantic Web Services (SWS) and BPM. As in the Process Mining case, SBPM and Business Network Management are complementing approaches with combinable technology stacks.…”

Section: Related Workmentioning

confidence: 99%

Towards a Business Network Management

Ritter¹

2013

Lecture Notes in Business Information Processing

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Abstract. Enterprises are part of value chains consisting of crossenterprise business processes forming large business networks of customers, vendors, partners and competitors. These business process networks run on (technical) integration networks, which are semantically interlinked with the processes, while both are correlated to organizational (social) networks, consisting of technical and business domain experts. The insight into these networks promise a competitive advantage through the visibility into the linked enterprise data. However, this information is hidden in complex, dynamic and heterogeneous enterprise domains.In this position paper, we introduce the new domain of Business Network Management (BNM), which strives to make business networks visible within network views and sets them into context with each other. For that, we extend the Network Mining (NM) domain by a virtualized network approach towards a BNM. That means automatic discovery, mining and inference capabilities are combined with expert knowledge from different domains to compute the networks and a semantic correlation between entities of different perspectives. We comprehensively define the domain and discuss a system implementation, which we evaluated in a real-world customer case.

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Organisational Ontology Framework for Semantic Business Process Management

Cited by 26 publications

References 7 publications

Formal Ontologies Meet Industry

Formal Ontologies Meet Industry

From network mining to large scale business networks

Towards a Business Network Management

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