In the past two decades, the use of ontologies has grown accompanied by a diversity in ontological representations and applications to more comprehensive domains. Knowledge engineers have found it expeditious to break down large (monolithic) ontologies to work with smaller fragments. Ontology modularization is the process of extracting a fragment, or "module", from an ontology, based on predefined requirements. Due to both the diversity in ontological representations and motivations for modularizing, the body of research on ontology modularization techniques has become extremely large and may be intimidating to the novice ontology researcher. The objective of the paper is to present a comprehensive, albeit high-level, review of ontology modularization techniques. A systematic literature review covering January 1st 2000 to July 31st 2020 was performed to find and classify papers on ontology modularization techniques. The techniques exhibiting certain properties with respect to several features were assessed, and the modularization techniques were classified with a multi-dimensional perspective. The classifications are intended to guide one to a suitable modularization process in accordance with the requirements. The limitations of ontology modularization techniques are highlighted in the conclusion, and characteristics of a desirable framework for an ontology representation that would be best-suited for modularization are presented.

Workflow management systems (WfMS) can be used to manage complex processes, such as those described by Clinical Practise Guidelines (CPG). Such processes involve a variety of stakeholders, however, frequently their interfaces are not suited to the needs of the stakeholders involved. Here we propose that WfMSs be integrated with tools to build a variety of interfaces to meet the needs of different users. Using a CPG for the management of hypertension as a case study, we give examples of user-friendly interfaces which can be built easily using our domain specific language, and which integrate with our WfMS. One interface guides the clinician in the management of the disease, allowing her him the opportunity to view and interact with the process in a more holistic fashion, recording and recalling information relevant to the patient or the task. A second interface is more suited to the patient for the self management of lifestyle parameters, while other interfaces can be used by the patient, the clinician or the manager to represent trends or aggregate data.

Ontology based knowledge management systems have a lot of potential: their applicability ranges from artificial intelligence, e.g., for knowledge representation and natural language processing, to information integration and retrieval systems, requirements analysis, and, most lately, to semantic web applications and workflow management systems. However the huge complexity of reasoning for ontologies with large TBoxes and/or ABoxes is often a barrier to their applicability in real-world settings especially those which are time sensitive. Materialization is a promising solution for scalable reasoning over ontologies with large ABoxes as it derives the implicit knowledge of an ontology and makes it available in a relational database. Although materialization can reduce the query answering time of an ontology, it has limitations in applications which require frequent update to the knowledge base. To overcome this problem, we developed a tool for incremental materialization which identifies the fragment of the ontology that needs to be updated due to the ABox or TBox change, thereby reducing the complexity of the exhaustive forward chaining required.

A workflow model is an abstract representation of a real life workflow and consists of interconnected tasks depicting the desired executions of real life activities. Time information is an important aspect of many safety-critical workflows. This paper presents a new formal diagrammatic approach to timed workflow modelling involving principles from model-driven engineering. The approach extends the Diagram Predicate Framework, which is based on category theory and graph transformations, for the specification of workflow modelling formalisms. We develop a transition system to represent the dynamic semantics involving time in which transitions are described by specification transformations between instances. To model time, we use predicates for time delay and duration with transition rules for time advancement.

Abstract Healthcare workflows (careflows) involve complex, distributive processes with a high degree of variability. There are ubiquitous communication and enormous data and knowledge management requirements and the processes involve complex timing requirements, and are safety critical. Designing these processes and managing their performance is difficult and error‐prone. Using verification techniques such as model checking, which are mathematical methods of proving correctness, we can reduce errors by ensuring that process designs satisfy their specifications. We describe a prototype next generation multithreaded model checker to reason about processes in careflows, sensitive to patient preferences and the goals of the careteam using a timed temporal logic extended with modalities of beliefs, desires, and intentions. Copyright © 2011 John Wiley & Sons, Ltd.

A major challenge for ontology integration is to deal with inconsistencies. Existing merging tools are based on classical logic and are forced to avoid inconsistencies (to prevent the logic from becoming explosive) which may cause valuable information loss. However, inconsistent information may serve as an integral component in healthcare systems to give a full clinical perspective: any information loss is undesirable. In this paper we discuss various implementation issues for the development of a prototype merging system which will provide an inconsistency-tolerant reasoning mechanism applicable to the healthcare domain.

A calculus of typed relations subsuming the classical relational database theory is presented. An associated sound and complete deduction mechanism is developed. The formulation is generalized to deal with nondeterministic databases and information relations in the rough set-style.

Using a relational approach, we investigate the implication problem for dependencies for information relations, focusing on functional dependencies, association rules and multivalued dependencies. We develop a Rasiowa/Sikorski-style relational calculus and show that the associated tableaux style of reasoning gives a decidable procedure for each of the three kinds of inference problems under consideration. This work has applications to classical database theory and to Rough Set Theory. The techniques may be generalized to the many other data dependencies which have formulations via binary relations and they can be applied to other information relations which arise in the study of incomplete information.

Abstract In this paper we give relational semantics and an accompanying relational proof theory for full Lambek calculus (a sequent calculus which we denote by FL). We start with the Kripke semantics for FL as discussed in [11] and develop a second Kripke-style semantics, RelKripke semantics, as a bridge to relational semantics. The RelKripke semantics consists of a set with two distinguished elements, two ternary relations and a list of conditions on the relations. It is accompanied by a Kripke-style valuation system analogous to that in [11]. Soundness and completeness theorems with respect to FL hold for RelKripke models. Then, in the spirit of the work of Orlowska [14], [15], and Buszkowski and Orlowska [3], we develop relational logic RFL. The adjective relational is used to emphasize the fact that RFL has a semantics wherein formulas are interpreted as relations. We prove that a sequent Γ → α in FL is provable if and only if a translation,t(γ1● … ● γn⊃ α)ευu, has a cut-complete fundamental proof tree. This result isconstructive: that is, if a cut-complete proof tree fort(γ1● … ● γn⊃ α)ευuis not fundamental, we can use the failed proof search to build a relational countermodel fort(γ1● … ● γn⊃ α)ευuand from this, build a RelKripke countermodel for γ1● … ● γn⊃ α. These results allow us to add FL, the basic substructural logic, to the list of those logics of importance in computer science with a relational proof theory.

Using formally intuitionistic logic coupled with infinitary logic and the completeness theorem for coherent logic, we establish the validity, in Grothendieck toposes, of a number of well-known, classically valid theorems about fields and ordered fields. Classically, these theorems have proofs by contradiction and most involve higher order notions. Here, the theorems are each given a first-order formulation, and this form of the theorem is then deduced using coherent or formally intuitionistic logic. This immediately implies their validity in arbitrary Grothendieck toposes. The main idea throughout is to use coherent theories and, whenever possible, find coherent formulations of formulas which then allow us to call upon the completeness theorem of coherent logic. In one place, the positive model-completeness of the relevant theory is used to find the necessary coherent formulas. The theorems here deal with polynomials or rational functions (in s indeterminates) over fields. A polynomial over a field can, of course, be represented by a finite string of field elements, and a rational function can be represented by a pair of strings of field elements. We chose the approach whereby results on polynomial rings are reduced to results about the base field, because the theory of polynomial rings in s indeterminates over fields, although coherent, is less desirable from a model-theoretic point of view. Ultimately we are interested in the models. This research was originally motivated by the works of Saracino and Weispfenning [SW], van den Dries [Dr], and Bunge [Bu], each of whom generalized some theorems from algebraic geometry or ordered fields to (commutative, von Neumann) regular rings (with unity).