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Das Corporate Semantic Web fokussiert auf die Anwendung semantischer Web Technologien und Methoden im Unternehmensumfeld. In diesem Kapitel sollen die Beziehungen des Corporate Semantic Web zu angrenzenden Anwendungsgebieten geklart werden. Dazu wird zunachst eine grundlegende Begriffsklarung vorgenommen, um darauf aufbauend das Corporate Semantic Web gegenuber anderen verwandten Gebieten, wie dem Public Semantic Web, Social Semantic Web und Pragmatic Web, einzuordnen.

Dieses Kapitel fuhrt in die grundlegenden Vorgehensweisen der agilen Ontologieentwicklung ein und stellt derzeit existierende Ansatze und bislang gewonnene Erkenntnisse vor. Vor- und Nachteile agiler sowie klassischer, sequentieller Vorgehensmodelle werden einander gegenubergestellt. Schlieslich wird dem Leser eine konkrete Entscheidungshilfe im Hinblick auf die Frage „agiles oder klassisches Vorgehen?“ an die Hand gelegt.

Over the last decade, scientific workflows have been become a remarkable paradigm, which integrates distributed heterogeneous computational and data resources and assists scientists to perform data management, analysis, simulation in silico experiments. However, compared to traditional business workflows, scientific processes still haven’t been widely addressed and shared because of their extra requirements. In this paper, inspired by the spirit of subject-oriented business process management (S-BPM), we propose a rule agent-oriented approach to model weakly-structured scientific processes, where each agent has an internal behavior and the scientific workflow execution is driven by the messaging between distributed rule agents. As a proof-of-concept implementation we use the Web rule language Prova to declaratively represent the knowledge-intensive scientific logic as semantic rules, wrapped in the agents, and to support message-driven conversation-based interactions between these rule-based agents.

Scientific workflows streamline large-scale, complex scientific processes and enable different parts of a process to be systematically and efficiently executed on distributed resources. In this paper, we propose an event-driven framework for scientific workflows, which goes beyond the typical paradigm of global ECA (Event-Condition-Action) rules and executes scientific processes in terms of event message-driven conversations between rule agents. The behavioral reaction logic implemented by messaging reaction rules in combination with derivation rules used to represent complicated scientific conditional logic provides a highly expressive, scalable and flexible way to define complex scientific workflow patterns. Finally, a prototype system based on a Web rule engine Prova and a tool for rule-based collaboration Rule Responder is demonstrated.

Instead of focusing on the orchestration of low-level computational intensive tasks in efficiency critical structured scientific processes, as most of available scientific workflow systems do, this work explicitly addresses the coordination and decision-centric higher levels of weakly-structured scientific workflows supporting the choreography of human agents and IT services/agents in their scientific problem solving tasks. From a technical perspective, this work proposes a rule-based agent framework, which exploits the benefits of both the declarative knowledge representation with rules and ontologies and the abstraction with multi-agent technology to support the dynamic and adaptive execution of weakly-structured scientific workflows. Based on the evaluation in terms of the workflow patterns, the rule-based workflow specification in this work demonstrates a high expressiveness level required to represent different types of tasks. The concrete use cases from different scientific domains implemented by the framework also demonstrate that the work fulfills the requirements of weakly-structured scientific workflows.

Most of the semantic content available has been generated automatically by using annotation services for existing content. Automatic annotation is not of sufficient quality to enable focused search and retrieval: either too many or too few terms are semantically annotated. User-defined semantic enrichment allows for a more targeted approach. We developed a tool for semantic annotation of digital documents and conducted an end-user study to evaluate its acceptance by and usability for non-expert users. This paper presents the results of this user study and discusses the lessons learned about both the semantic enrichment process and our methodology of exposing non-experts to semantic enrichment.

The Internet is more than a web of computers and more than a web of documents. From a pragmatic point of view it is interesting what people do with the Internet and how. Actions and events have a meaning in the context of a process or practice as enveloping a set of shared norms. The norms apply to behavior, but also to interpretation and evaluation, and can be represented and implemented using rule-based systems.

RuleML is a family of XML languages whose modular system of schemas permits high-precision (Web) rule interchange. The family's top-level distinction is deliberation rules vs. reaction rules. In this paper we address the Reaction RuleML subfamily of RuleML and survey related work. Reaction RuleML is a standardized rule markup/serialization language and semantic interchange format for reaction rules and rule-based event processing. Reaction rules include distributed Complex Event Processing (CEP), Knowledge Representation (KR) calculi, as well as Event-Condition-Action (ECA) rules, Production (CA) rules, and Trigger (EA) rules. Reaction RuleML 1.0 incorporates this reactive spectrum of rules into RuleML employing a system of step-wise extensions of the Deliberation RuleML 1.0 foundation.

This chapter introduces Rule Responder and its applications. Rule Responder is a framework for specifying virtual organizations as semantic multi-agent systems that support collaborative teams. It provides the infrastructure for rule-based collaboration between the distributed members of such a virtual organization. Human members of an organization are assisted by (semi-)autonomous rule-based agents, which use Semantic Web rules to describe aspects of their owners' derivation and reaction logic. To implement different distributed system/agent toplogies with their negotiation/coordination mechanisms Rule Responder instantiations employ three core classes of agents - Organizational Agents (OA), Personal Agents (PAs), and External Agents (EAs). The OA represents goals and strategies shared by its virtual organization as a whole, using a rulebase that describes its policies, regulations, opportunities, etc. Each PA assists a group or person of the organization, semi-autonomously acting on their behalf by using a local knowledge base of rules defined by the entity. EAs can communicate with the virtual organization by sending messages to the public interfaces of the OA. EAs can be human users using, e.g., Web forms or can be automated services/tools sending messages via the multitude of transport protocols of the underlying enterprise service bus (ESB) middleware. The agents employ ontologies in their knowledge bases to represent semantic domain vocabularies, normative pragmatics and pragmatic context of conversations and actions, as well as the organizational semiotics., Series: Studies in Computational Intelligence

In Rule-based Event Processing and Complex Event Processing (CEP), many areas of software development re-use existing technologies and methodologies, allowing their related standards to be re-used. Other standards may be required to be developed to replace or augment existing standards. This paper introduces a general reference model for CEP standards with which existing and required standards will be discussed.

The growing importance of Web-based service organizations and agile enterprise service networks creates a need for the optimization of semi- or unstructured, decision-centric service processes. These decision-centric processes often contain more event-driven and situationaware behavior, more non-standard knowledge intensive cases and eventdriven routings, and more variability and agility than traditional processes. Consequently, systems supporting these decision-centric service processes require much more degrees of freedom than standard BPM systems. While pure syntactic BPM languages such as OASISWS-BPEL and OMG BPMN addresses the industry's need for standard service orchestration semantics they provide only limited expressiveness to describe complex decision logic and conditional event-driven reaction logic. In this paper we propose a heterogenous service-oriented integration of rules (decision rules and complex event processing reaction rules) into BPM to describe rule-based business processes. This leads to a declarative rule-based Semantic BPM (SBPM) approach, which aims at agile and adaptive business process execution including enforcement of nonfunctional SLA properties of business services via rules.

The Rule Responder SymposiumPlanner system supports topic-oriented collaboration between the distributed members of a virtual organization. Each member (or small team of members) is assisted by a semi-autonomous rule-based personal agent, which uses Semantic Web rules to capture aspects of the member's (or team's) derivation and reaction logic. SymposiumPlanner is a series of Rule Responder use cases for supporting the RuleML Symposia (2007-2011) by coordinating personal agents that assist the symposium chairs, intelligently answering questions from people interested in the symposium. In this paper, we introduce principles of SymposiumPlanner and make suggestions about its future development, mainly for RuleML-2012, and about further Rule Responder use cases., 5th International Symposium on Rules: Research Based and Industry Focused (RuleML 2011), November 3-5, 2011, Fort Lauderdale, Florida, USA, Series: Lecture Notes in Computer Science; no. 7018

The paper contains an overview of the roles played by rules and rule-based systems in distributed and multi-agent systems. These roles include an overview of traditional and newly emerging application areas as well as internal agent architectures and frameworks implementing these architectures.

This lecture script gives an introduction to rule based knowledge representation on Web. It reviews the logical foundations of logic programming and derivation rule languages and describes existing Web rule standard languages such as RuleML, the W3C Rule Interchange Format (RIF), and the Web rule engine Prova.

The recently coined term «Event-Driven Business Process Management» (EDBPM) is nowadays an enhancement of BPM by new concepts of Service Oriented Architecture, Event Driven Architecture, Software as a Service, Business Activity Monitoring and Complex Event Processing (CEP). In this context BPM means a software platform which provides companies the ability to model, manage, and optimize these processes for significant gain. As an independent system, CEP is a parallel running platform that analyses and processes events. The BPM- and the CEP-platform correspond via events which are produced by the BPM-workflow engine and by the – if distributed - IT services which are associated with the business process steps. Also events coming from different event sources in different forms can trigger a business process or influence the execution of a process or a service, which can result in another event. Even more, the correlation of these events in a particular context can be treated as a complex, business level event, relevant for the execution of other business processes or services. A business process – arbitrarily fine or coarse grained – can be seen as a service again and can be “choreographed” with other business processes or services, even between different enterprises and organizations.

RuleML is a family of languages, whose modular system of XML schemas permits high-precision Web rule interchange. The family's top-level distinction is deliberation rules vs. reaction rules. Deliber- ation rules include modal and derivation rules, which themselves include facts, queries (incl. integrity constraints), and Horn rules (incl. Data- log). Reaction rules include Complex Event Processing (CEP), Knowl- edge Representation (KR), and Event-Condition-Action (ECA) rules, as well as Production (CA) rules. RuleML rules can combine all parts of both derivation and reaction rules. This allows uniform XML serialization across all kinds of rules. After its use in SWRL and SWSL, RuleML has provided strong input to W3C RIF on several levels. This includes the use of `striped' XML as well as the structuring of rule classes into sublan- guages with partial mappings between, e.g., Datalog RuleML and RIF- Core, Hornlog RuleML and RIF-BLD, as well as Production RuleML and RIF-PRD. We discuss the rationale and key features of RuleML 1.0 as the overarching specification of Web rules that encompasses RIF RuleML as a subfamily, and takes into account corresponding OASIS, OMG (e.g., PRR, SBVR), and ISO (e.g., Common Logic) specifications., The 4th International Web Rule Symposium: Research Based and Industry Focused (RuleML - 2010), October 21-23, 2010, Washington, DC, USA, Series: Lecture Notes in Computer Science; no. 6403

One of the critical success factors of event-driven systems is the capability of detecting complex events from simple and ordinary event notifications. Complex events which trigger or terminate actionable situations can be inferred from large event clouds or event streams based on their event instance sequence, their syntax and semantics. Using semantics of event algebra patterns defined on top of event instance sequences for event detection is one of the promising approaches for detection of complex events. The developments and successes in building standards and tools for semantic technologies such as declarative rules and ontologies are opening novel research and application areas in event processing. One of these promising application areas is semantic event processing. In this work we describe our research on semantic rule-based complex events processing.

Reaction rules and event processing technologies play a key role in making business and IT / Internet infrastructures more agile and active. While event processing is concerned with detecting events from large event clouds or streams in almost real-time, reaction rules are concerned with the invocation of actions in response to events and actionable situations. They state the conditions under which actions must be taken. In the last decades various reaction rule and event processing approaches have been developed, which for the most part have been advanced separately. In this paper we survey reaction rule approaches and rule-based event processing systems and languages.

It is commonly accepted that separating the declarative rules from the procedural code of an application makes that application easier to understand and easier to modify. What has been lacking is a standard representation for rules --- until now. Using the W3C's Rule Interchange Format [1], rules will be exchanged and revised among three different rule systems: ILOG JRules [2], Oracle [3], and Prova [4].

In this paper we evolve a rule based approach to SLA representation and management which allows separating the contractual business logic from the application logic and enables automated execution and monitoring of SLA specifications. We make use of a set of knowledge representation (KR) concepts and combine adequate logical formalisms in one expressive formal framework called ContractLog.