The International RuleML Symposium on Rule Interchange and Applications

Orlando, Florida: October 30-31, 2008

Keynote Speakers

Rule Interchange Format: The Framework

Picture of Michael Kifer


The Rule Interchange Format (RIF) is a W3C activity aimed at developing a Web standard for exchanging rules. The need for rule-based information processing on the Semantic Web has been felt ever since RDF was introduced in the late 90's. As ontology development picked up pace this decade and the limitations of OWL became more apparent, rules were firmly put back on the agenda. RIF is therefore a major opportunity for the introduction of rule based technologies into the main stream of knowledge representation and information processing.

Despite its humble name, RIF is not just a format and is not primarily about syntax. It is an extensible framework for rule-based languages, called RIF dialects, which includes precise and formal specification of the syntax, semantics, and XML serialization of the dialects. In this talk we will discuss the main principles behind RIF, introduce the RIF extensibility framework, and present the Basic Logic Dialect---the only fully developed RIF dialect so far. We will also discuss the opportunities for community involvement in furthering this standard.



Michael Kifer is a Professor with the Department of Computer Science, State University of New York at Stony Brook, USA. He received his Ph.D. in Computer Science in 1984 from the Hebrew University of Jerusalem, Israel, and the M.S. degree in Mathematics in 1976 from Moscow State University, Russia.

Professor Kifer's interests include Web information systems, knowledge representation, and database systems. He has published four text books and numerous articles in these areas. Professor Kifer serves on the editorial boards of several computer science journals and chaired a number of conferences. Twice, in 1999 and 2002, he was a recipient of the prestigious ACM-SIGMOD "Test of Time" awards for his works on F-logic and object-oriented database languages. In 2006, he was a Plumer Fellow at Oxford University's St. Anne's College and in 2008 he received Chancellor's Award for Excellence in Scholarship.


The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems

Picture of David Luckham
  • David Luckham
  • Research Professor of Electrical Engineering (Emeritus)
  • Department of Electrical Engineering
  • Stanford University, USA


This talk is about the rise of Complex Event Processing (CEP) as we know it today, its historical roots and its current position in commercial markets. Some possible long-term future roles of CEP in the Information Society will be discussed along with the need to develop rule-based event hierarchies on a commercial basis to make those applications possible. The talk will try to make the point that "Rules are everywhere" and that mathematical formalisms cannot express all the forms that are in use in various event processing systems.


Professor Luckham's research and consulting activities in software technology include multi-processing and business processing languages, event-driven systems, complex event processing, commercial middleware, program verification, systems architecture modelling and simulation, and artificial intelligence (automated deduction and reasoning systems).

He has held faculty and invited faculty positions in both mathematics and computer science at eight major universities in Europe and the United States including Stanford, Harvard and UCLA. Until 1999, he was a member of the Computer Systems Laboratory at Stanford University, and directed the Program Analysis and Verification project. He was one of the founders of Rational Software, Inc., in 1981. He has published four books and over 100 technical papers; two ACM/IEEE Best Paper Awards, several papers are now in historical anthologies and book collections. His latest book is an introduction to complex event processing, The Power of Events.


Event and Process Semantics will Rule

Picture of Paul Haley
  • Paul Haley
  • Chairman, Haley Systems, Inc.
  • President, Automata, Inc.


The convergence of business rules with business process management (BPM) has been predicted for many years and is now a matter of fact. Every major BPM vendor has incorporated or acquired rules technology within their products and platforms. However, most rules offerings are only loosely integrated with processes at the task level. The use of business rules remains largely confined to managing isolated decisions services. Weak integration and isolation effectively relegates rules to an implementing role rather than a first class citizen in the capture and management of enterprise knowledge.

As the largest vendors bring their rules offerings to market and as standards from the W3C and OMG mature to adequacy, the opportunity for vendor-agnostic business rules management systems (BRMS) approaches. And continued improvement in end-user accessibility of BRMS promises ever less technical and ever more semantic expression and management of enterprise knowledge, including process and service models in addition to data models and business rules.

The ability to interchange more semantic models across major vendor offerings promises to dramatically increase the market demand for reusable, enterprise-relevant knowledge. But as knowledge becomes increasingly declarative and independent of implementations, it naturally becomes more ontological. Unfortunately, current ontological technologies are functionally inadequate from a business process or event processing perspective. These inadequacies include the lack of ontology for events, processes, states, actions, and other concepts that relate to change over time. Without such ontologies, rules or logic that govern processes or react to events must remain at the level of procedural implementation rather than declarative knowledge.

Until BRMS understand rules that refer to activities and events occurring within business processes, business rules applications will remain largely confined to discrete decisions, such as encapsulation within a decision service. By incorporating an adequate ontology of events and action, however, the knowledge management capabilities first developed in BRMS will broaden to encompass much of BPM and complex event processing (CEP). Given the fact that BRMS has been incorporated by the dominant platform vendors, modeling should move up from the relatively narrow perspective of a BRMS into the broader context of BPM and CEP.

The migration of business rules management into event and process contexts will emphasize the separation of business rules into ontology versus behavior. Modeling event-driven and business processes will correspond to defining ontology. Implementing event-driven and business processes will invoke behaviors at runtime. The ontology will be the same for BPM, CEP, or the BRMS, as will the behaviors. But the BRMS will know what is happening in terms of events and processes and it will know what processes it can invoke and what events it can signal.

As ontology management becomes increasingly relevant across application development, the limitations of related standards will also come into clearer focus. Commercial BRE are, for the most part, production rule systems that emphasize action over logic. This is best addressed by OMG's production rule representation (PRR) standard. But PRR is an isolated standard that includes no support for ontology or logic. W3C's web-ontology language (OWL) and rule interchange format (RIF) standards address ontology and logic, but not change or action. The same is true of OMG's SBVR, which emphasizes linguistics, in addition to ontology and logic, albeit in a way that remains disconnected with the OMG stack, including PRR.

Bridging events, processes and other aspects of reality that occur and change over time and incorporating action is a fundamental challenge for semantic technologies, especially formal logic, that must be addressed in a practical manner before rules standards and semantic technologies will bear substantial fruit in enterprise contexts.



Paul Haley is a veteran software technologist and business developer specializing in Artificial Intelligence with decades of experience selling, developing and applying advanced technology in securities, banking, insurance, healthcare, telecommunications, and government applications.

Mr. Haley managed the development of Inference Corporation's Automated Reasoning Tool (ART) from which CLIPS and JESS are derived. Afterwards, he founded Haley Systems which Gartner, IDC, and Forrester recognized as the visionary technology leader in business rules, especially emphasizing natural language management of ontological and rule-based knowledge by non-programmers. After selling Haley to Ruleburst, Paul founded Automata, Inc. which provides services concerning semantic and artificial intelligence technologies.


Hyper Logic Programs in SILK: Redefining the KR Playing Field for Business and VLKB

Picture of Benjamin Grosof
  • Benjamin Grosof
  • Senior Research Program Manager, Knowledge Systems
  • Vulcan, Inc.


We overview the approach taken by the SILK system, a new, highly ambitious effort to redefine the knowledge representation (KR) playing field for business rules and rule-based process management. The newest part of Vulcan Inc.'s Project Halo, SILK aims to provide key infrastructure for widely-authored VLKBs (Very Large Knowledge Bases) for business and science that answer questions, proactively supply information, and reason powerfully. SILK includes a highly expressive, fully semantic, rule language based expressively on the Hyper Logic Programs KR, together with components for reasoning, web knowledge interchange, and collaborative knowledge acquisition.

Hyper LP newly synergizes several major strands of pure-research progress in KR based on extensions of declarative logic programs, which are the core KR of RuleML and Rule Interchange Format (RIF) as well as of databases (SQL, XQuery, and SPARQL) and most commercial implementations of OWL ontologies. Hyper LP adds: prioritized defaults cf. courteous and Defeasible Logic; higher-order and frames cf. F-Logic; tight integration of weakened full classical logic (including OWL) cf. generalized Description LP; actions and events cf. production rules, Event-Condition-Action rules, and Situated/Production LP.

Key challenges for SILK include exploiting natural language in user interaction, parallelism in reasoning, and disjunction in expressiveness. We discuss prospects for the SILK approach to effectively interchange and integrate a high percentage of the world's structured knowledge starting from today's legacy forms. "SILK" stands for "Semantic Inferencing on Large Knowledge", what the next generation Web will be spun from.



Benjamin Grosof is a senior research program manager at Vulcan Inc., the company of Paul G. Allen (co-founder of Microsoft). There he conceived and leads a new large research program in the area of rule-based semantic technologies and artificial intelligence. Prior to his move to Vulcan in 2007, he was a professor of Information Technology at MIT, in the Sloan School of Management. His research involved the creation of technologies for the new generation web, in which e-services and business communication are more knowledge- and agent-based. In particular, he has pioneered semantic technology and standards for rules, their combination with ontologies, and the Semantic Web. He co-founded the influential RuleML industry standards design effort, and the International Conference on Rules and Rule Markup Languages for the Semantic Web. He was lead inventor of the rule-based technique which rapidly became the currently dominant approach to commercial implementation of OWL.

Prior to joining MIT Sloan in 2000, he was a senior research scientist, in software, at IBM T.J. Watson Research Center (12 years there), where most recently he conceived and led IBM CommonRules and co-led its application piloting for rule-based XML agent contracting in EECOMS, a $29 Million NIST industry-government consortium project on manufacturing supply chain collaboration. His notable technical contributions also include fundamental advances in rule-based intelligent agents, conflict handling for rules, rule-based security authorization, and integration of rules with machine learning. He is author of over 50 refereed publications, three major industry software releases, and two patents. His background includes two years in software startups, a PhD in Computer Science (specialty Artificial Intelligence) from Stanford University, and a BA in Applied Mathematics (specialty Economics and Management Science) from Harvard University.