RuleML 2016 Industry Track Panel Discussion Session

July 6, 2016 4:05 AM
At the close of Friday's (July 8, 2016) program at, the Industry Track will host a panel discussion session with the theme of "Looking to the Future of Rules in Industry".
Industry Track Panel members include:

Mark Proctor of Red Hat, Inc.
Adrian Pascke of Fraunhofer FOKUS and AG Corporate Semantic Web at the Freie Universitaet Berlin
Benjamin Grosof of Coherent Knowledge
Tom Debevoise of Signavio, Inc.
Dörthe Arndt of iMinds

The moderator will be Tara Athan of Athan Services and
AG Corporate Semantic Web.

In order to facilitate a lively discussion, we request the submission of questions and topics of discussion from all interested parties.
Please use the comment section below, if possible; otherwise, email to .

Submit your application at Challenge and win 500USD

May 23, 2016 1:04 PM
10th International Rule Challenge 2016, part of the 10th International Web Rule Symposium (RuleML 2016), Stony Brook University, New York, USA, July 8-9, 2016 Paper submission: June 1st, 2016
As in previous editions, RuleML Inc. will offer a cash prize:
RuleML Challenge Award for the Best Demo Application - 500 USD

Important Dates

  • Paper submission: June 1st, 2016
  • Notification: June 13th, 2016
  • Camera ready: June 19th, 2016
  • Rule Challenge 2016: July 8-9, 2016
This year, the challenge presents seven main themes to inspire participant submissions (of course, submissions on other themes are welcome as well).

Rules in Retail

  • When a customer enters the store and an "offer of the day" is available, then push only one welcome notification and display the offer of the day.
  • When a customer watches a specific product, then push related photos and information, including social media reactions, directly to their device.

Rules in Tourism

  • Deliver a welcome message to POI visitors as they arrive nearby.
  • When a visitor leaves a room in the museum, then push notifications regarding the next recommended room, based on visitors' preferences and previous visit history.
  • When a visitor completes the tour, then push goodbye messages and notify on upcoming/partner exhibitions.

Rules in Transportation

  • When arriving at car parking, then push a notification on available places.
  • When selecting destination and inside a bus station, then display bus data (arrival time, notices).
  • When bus nears destination, then push notification on time to arrival and suggest accommodations.

Rules in Geography

  • A region X is part of a region Y if and only if all regions that connect to X also connect to Y
  • Two regions X and Y are overlapped if and only if there exists a region Z such that Z is part of X and Z is part of Y

Rules in Location-Based Search

  • If less than or equal to k POIs of type X (e.g., Restaurants) are found, then zoom in/out on the map to the axis-aligned minimum bounding box of all POIs.
  • If more than k POIs of type X are found, then zoom in/out on the map to the axis-aligned minimum bounding box of the k-nearest POIs.
  • If the POIs searched for are of type X then suggest to the user subtypes of X (e.g., Italian, Greek) for a subsequent (i.e., refined) search.

Rules in Insurance Regulation

  • If an item is perishable and is delivered more than 10 days after the scheduled delivery date, then it may be rejected.
  • Each tax schedule must have electronic signatures from two managers.
  • If an inspector believes a vehicle is repairable then process the claim as a repair; otherwise process the claim as a total loss.

Rules in Medicine

  • If a Type II diabetes patient's current level of HbA1c is high, then the patient's current treatment is ineffective.
  • Issue medical alerts to patients (e.g., on a mobile device), based on health trend analysis and personalizable health value limits.
  • If patient has low back pain without radicular pain or neurologic findings, then consider urine drug screening and repeat neurologic test.

Rules in Ecosystem Research

  • If a plot in a monitoring network satisfies a number of prespecified requirements, such as being a long distance off from any other plot, then it is eligible for statistical analysis.
  • If the percentage of a target species on a plot exceeds a certain threshold, then the plot is treated differently in statistical analysis than plots where the target species is less abundant.
  • The percentage of a target species on a plot must not vary throughout the analysis.

Enabling Reasoning with LegalRuleML

May 23, 2016 10:28:20 AM
New CS Department,
Engineering Dr,
11794 Stony Brook, NY
From Jul 8, 2016 12:30 PM
To Jul 8, 2016 1:00 PM
A paper by Ho-Pun Lam, Mustafa Hashmi, and Brendan Scofield (Data61, CSIRO | NICTA)
Abstract. This paper presents an approach for the specification and implementation of translating legal norms represented using LegalRuleML to a variant of Modal Defeasible Logic. From its logical form, legal norms will be transformed into a machine readable format and eventually implemented as executable semantics that can be reasoned about depending on the client's preference.

Business Rules Uncertainty Management with Probabilistic Relational Models

May 23, 2016 9:55:44 AM
New CS Department,
Engineering Dr,
11794 Stony Brook, NY
From Jul 8, 2016 12:00 PM
To Jul 8, 2016 12:30 PM
A paper by Hamza AGLI (IBM France), Philippe BONNARD (IBM France), Christophe GONZALES (Sorbonne Universite) and Pierre-Henri WUILLEMIN (Sorbonne Universite)
Abstract. Object-oriented Business Rules Management Systems (OO-BRMS) are a complex applications platform that provides tools for automating day-to-day business decisions. To allow more sophisticated and realistic decision-making, these tools must enable Business Rules (BRs) to handle uncertainties in the domain. For this purpose, several approaches have been proposed, but most of them rely on heuristic models that unfortunately have shortcomings and limitations. In this paper we present a solution allowing modern OO-BRMS to effectively integrate probabilistic reasoning for uncertainty management. This solution has a coupling approach with Probabilistic Relational Models (PRMs) and facilitates the interoperability, hence, the separation between business and probabilistic logic. We apply our approach to an existing BRMS and discuss implications of the knowledge base dynamicity on the probabilistic inference.

Spatial Reasoning in Constraint Logic Programming based on Numerical Optimisatio

May 23, 2016 9:48:09 AM
New CS Department,
Engineering Dr,
11794 Stony Brook, NY
From Jul 8, 2016 11:30 AM
To Jul 8, 2016 12:00 PM
A paper by Carl Schultz (The DesignSpace Group, University of Münster) and Mehul Bhatt (University of Bremen)
Abstract. In this paper we formulate (qualitative) spatial reasoning within the framework of numerical optimisation, and develop an approach that extends Constraint Logic Programming (CLP) to support variables that range over spatial domains. The crux of our approach is extending standard unification by the mechanism of attributed variables, and using specialised numerical optimisation algorithms in a stateless manner. We prove that our approach is fully consistent with the semantics of CLP, and demonstrate a range of powerful spatial reasoning features.