Harold Boley

Digital Ecosystems: Principles and Semantics

Digital ecosystems transcend the traditional, rigorously defined, collaborative environments from centralised, distributed or hybrid models into an open, flexible, domain cluster, demand-driven, interactive environment. A digital ecosystem is a newly networked architecture and collaborative environment that addresses the weakness of client-server, peer-to-peer, grid, and Web services. In this paper we provide an explanation of digital ecosystems, their analogy to ecological systems, architecture, swarm intelligence, and comparison to existing networked architecture. We then describe how digital ecosystems can benefit from semantic Web ontologies and rules. Finally, we discuss issues in the collaboration between semantically neighbouring digital ecosystems.

A Weighted-Tree Similarity Algorithm for Multi-Agent Systems in E-Business Environments

A tree similarity algorithm for match‐making of agents in e‐Business environments is presented. Product/service descriptions of seller and buyer agents are represented as node‐labeled, arc‐labeled, arc‐weighted trees. A similarity algorithm for such trees is developed as the basis for semantic match‐making in a virtual marketplace. The trees are exchanged using an XML serialization in Object‐Oriented RuleML. Correspondingly, we use the declarative language Relfun to implement the similarity algorithm as a parameterized, recursive functional program. Three main recursive functions perform a top‐down traversal of trees and the bottom‐up computation of similarity. Results from our experiments aiming to match buyers and sellers are found to be effective and promising for e‐Business/e‐Learning environments. The algorithm can be applied in all environments where weighted trees are used.

Collaborative filtering and inference rules for context‐aware learning object recommendation

Learning objects strive for reusability in e‐Learning to reduce cost and allow personalization of content. We show why learning objects require adapted Information Retrieval systems. In the spirit of the Semantic Web, we discuss the semantic description, discovery, and composition of learning objects. As part of our project, we tag learning objects with both objective (e.g., title, date, and author) and subjective (e.g., quality and relevance) metadata. We present the RACOFI (Rule‐Applying Collaborative Filtering) Composer prototype with its novel combination of two libraries and their associated engines: a collaborative filtering system and an inference rule system. We developed RACOFI to generate context‐aware recommendation lists. Context is handled by multidimensional predictions produced from a database‐driven scalable collaborative filtering algorithm. Rules are then applied to the predictions to customize the recommendations according to user profiles. The RACOFI Composer architecture has been deve...

Rule responder: RuleML-based agents for distributed collaboration on the pragmatic web

The Rule Responder project (responder.ruleml.org) extends the Semantic Web towards a Pragmatic Web infrastructure for collaborative human-computer networks. These allow semi-automated agents - with their individual (semantic and pragmatic) contexts, decisions and actions - to form corporate, not-for-profit, educational, or other virtual teams or virtual organizations. The project develops an effective methodology and an efficient infrastructure to interchange and reuse knowledge (ontologies and rules). Such knowledge plays an important role for (semi-automatically and contextually) transforming data, deriving new conclusions and decisions from existing knowledge, and acting according to changed situations or occurred (complex) events. Ultimately, this might put AI theories on distributed multiagent systems into larger-scale practice and might form the basis for highly flexible and adaptive Web-based service-oriented/service-component architectures (SOAs/SCAs).

The rule markup language: RDF-XML data model, XML schema hierarchy, and XSL transformations

Shared declarative aspects of Prolog and XML are examined. An XML version of pure Prolog is shown to be at the center of the Rule Markup Language. The RuleML data model uses Order-Labeled trees, combining the RDF and XML models. As part of RuleMLs hierarchy of sublanguages, the RuleML-Prolog DTD is developed into an XML Schema. XSLT (XSL Transformations) is employed for practical XML-to-XML and XML-to-(X)HTML transformation of Prolog on the Web.

Combining RDF Vocabularies for Expert Finding

This paper presents a framework for the reuse and extension of existing, established vocabularies in the Semantic Web. Driven by the primary application of expert finding, we will explore the reuse of vocabularies that have attracted a considerable user community already (FOAF, SIOC, etc.) or are derived from de facto standards used in tools or industrial practice (such as vCard, iCal and Dublin Core). This focus guarantees direct applicability and low entry barriers, unlike when devising a new ontology from scratch. The Web is already populated with several vocabularies which complement each other (but also have considerable overlap) in that they cover a wide range of necessary features to adequately describe the expert finding domain. Little effort has been made so far to identify and compare existing approaches, and to devise best practices on how to use and extend various vocabularies conjointly. It is the goal of the recently started ExpertFinder initiative to fill this gap. In this paper we present the ExpertFinder framework for reuse and extension of existing vocabularies in the Semantic Web. We provide a practical analysis of overlaps and options for combined use and extensions of several existing vocabularies, as well as a proposal for applying rules and other enabling technologies to the expert finding task.

OASIS LegalRuleML

In this paper we present the motivation, use cases, design principles, abstract syntax, and initial core of LegalRuleML. The LegalRuleML-core is sufficiently rich for expressing legal sources, time, defeasibility, and deontic operators. An example is provided. LegalRuleMLis compared to related work.

Distributed Trust Management for Validating SLA Choreographies

For business workflow automation in a service-enriched environment such as a grid or a cloud, services scattered across heterogeneous Virtual Organizations (VOs) can be aggregated in a producer-consumer manner, building hierarchical structures of added value. In order to preserve the supply chain, the Service Level Agreements (SLAs) corresponding to the underlying choreography of services should also be incrementally aggregated. This cross-VO hierarchical SLA aggregation requires validation, for which a distributed trust system becomes a prerequisite. Elaborating our previous work on rule-based SLA validation, we propose a hybrid distributed trust model. This new model is based on Public Key Infrastructure (PKI) and reputation-based trust systems. It helps preventing SLA violations by identifying violation-prone services at service selection stage and actively contributes in breach management at the time of penalty enforcement.

LegalRuleML: XML-based rules and norms

Legal texts are the foundational resource where to discover rules and norms that feed into different concrete (often XML-based) Web applications. Legislative documents provide general norms and specific procedural rules for eGovernment and eCommerce environments, while contracts specify the conditions of services and business rules (e.g. service level agreements for cloud computing), and judgments provide information about the legal argumentation and interpretation of norms to concrete case-law. Such legal knowledge is an important source that should be detected, properly modeled and expressively represented in order to capture all the domain particularities. This paper provides an extension of RuleML called LegalRuleML for fostering the characteristics of legal knowledge and to permit its full usage in legal reasoning and in the business rule domain. LegalRuleML encourages the effective exchange and sharing of such semantic information between legal documents, business rules, and software applications.

The Abstract Syntax of RuleML - Towards a General Web Rule Language Framework

This paper discusses the approach taken by the Rule Markup Language (RuleML) Initiative towards a general Web rule language framework and relates it to the MDA and UML by the Object Management Group (OMG). It also presents the abstract syntax of RuleML 0.85 as a MOF/UML model and considers the possibility to integrate RuleML with OCL and Action Semantics.