Corporate Semantic Web
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The initial vision of a global Semantic Web remains largely unfulfilled, facing problems like scalability, broader adoption of commonly shared ontologies, a lack of incentives to annotate content, as well as privacy and trust issues. Considering a corporate environment, which is more controlled, these problems do not arise to the same extent. In a corporation, there is a closed group of users and the management is able to enforce company guidelines regarding knowledge management, e.g. the adoption of ontologies. Compared to the public Semantic Web there are lesser requirements on scalability and the information circulating within a company can be more trusted in general.
Corporate Semantic Web addresses both the internal (e.g. enterprise members) and external side of an enterprise (e.g. customers), which may be either humans (employees or customers) or automated services (e.g. in business processes and enterprise service networks). It considers the semantic enhancement of information delivered to end-users as well as semantic applications, aiming at:
- facilitating the integration of information from mixed sources
- dissolving ambiguities in corporate terminology
- improving information retrieval thereby reducing information overload
- identifying relevant information with respect to a given domain
- providing decision making support
Pragmatic Point of View
While Semantic Web focuses primarily on fundamental technologies, Corporate Semantic Web focuses on pragmatic aspects of transferring semantic technologies into productive usage. Besides realizing semantic applications it also includes reviewing the economical aspects (e.g. cost models) of their development and management. Thus, it can help decision makers on the strategic, tactical, and operational level to understand the impact and benefit of semantic technologies.
There are three main areas of the Corporate Semantic Web: ontology engineering, semantic applications, and collaboration. Ontology engineering considers the efficient and effective development of ontologies (e.g. developing agile processes for ontology engineering) to lessen the costs of ontology development and maintenance. The area of semantic applications analyzes existing applications and evaluates to what extent they could benefit from semantic technologies and, finally realizes them, e.g., search on the basis of background knowledge (semantic search). Collaboration focuses on the human-centered aspects of knowledge management in corporate contexts. For example, it researches approaches for involving non-expert users in developing ontologies as well as semantically annotated content collaboratively and for extracting explicit knowledge from the interaction of users within enterprises.
All three parts work together in an integrative Corporate Semantic Web life cycle where (1) an application domain is modeled semantically resulting in ontologies and sets of rules (ontology engineering), (2) a semantic application is built on top of the semantically represented domain (semantic applications), and (3) the interaction of users with the semantic applications is used to evolve ontologies and rules to adapt them - and thus the applications - to changes in the environment (collaboration).
Automated Semantic Business Processes
The assumption behind Business Process Management (BPM) is that the uniqueness of an enterprise lies in how it manages and executes its business processes. Accordingly, business processes are the most valuable asset of an enterprise. Modern BPM often directly builds upon (i) IT Governance as a strategic instrument of the enterprise business strategy, (ii) IT Service Management (ITSM) describing the change of IT towards service and customer orientation, and (iii) IT Infrastructure Management (ITIM) focusing on the planning and efficient and effective delivery of IT services and products while meeting quality of service and security requirements. Corporate Semantic Web technologies offer methods and tools for the machine-readable and human-usable representation of knowledge to bridge between this technical IT service view and business processes. Thus, it allows the involvement of humans in these automated processes. The basic means of addressing this part are rules and ontologies, where rules declaratively describe business rules and IT policies and ontologies capture the application domain such as a business vocabulary. For example they might be used to model business processes or to implement Semantic Web Services (SWS) for Service Oriented Computing (SOC).
In particular in the realm of corporate collaboration, semantic technologies may offer support for semi-automatic knowledge evolution and dynamic integration of and access to distributed, heterogeneous information sources. By enabling organizations the extraction of implicit knowledge from corporate data as well as by a semantically meaningful representation of human expertise (corporate wisdom), Semantic Web technologies may be used for recognizing trends or problem solving within enterprises.
The first research group explicitly focusing on the Corporate Sementic Web was the ACACIA team at INRIA-Sophia-Antipolis, founded in 2002. Results of their work include the RDF(S) based Corese search engine, and the application of semantic web technology in the realm of E-learning.
Since 2008, the Corporate Semantic Web research group, located at the Free University of Berlin, focuses on the building blocks of a Corporate Semantic Web: Corporate Semantic Search, Corporate Semantic Collaboration, and Corporate Ontology Engineering.
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