scholarly journals An Ontology for Formal Models of Kinship

Author(s):  
Carmen Chui ◽  
Michael Grüninger ◽  
Janette Wong

The near ubiquity of family relationship ontologies in the Semantic Web has brought on the question of whether any formal analysis has been done in this domain. This paper examines kinship relationships that are normally overlooked in formal analyses of domain-specific ontologies: how are such ontologies verified and validated? We draw inspiration from existing work done in anthropology, where attempts have been made to formally model kinship as atemporal algebraic models. Based on these algebraic models, we provide an ontology for kinship written in first-order logic and demonstrate how the ontology can be used to validate definitions found in Canadian legal laws and data collection documentation.

2009 ◽  
Vol 19 (12) ◽  
pp. 3091-3099 ◽  
Author(s):  
Gui-Hong XU ◽  
Jian ZHANG

2011 ◽  
pp. 24-43
Author(s):  
J. Bruijn

This chapter introduces a number of formal logical languages which form the backbone of the Semantic Web. They are used for the representation of both ontologies and rules. The basis for all languages presented in this chapter is the classical first-order logic. Description logics is a family of languages which represent subsets of first-order logic. Expressive description logic languages form the basis for popular ontology languages on the Semantic Web. Logic programming is based on a subset of first-order logic, namely Horn logic, but uses a slightly different semantics and can be extended with non-monotonic negation. Many Semantic Web reasoners are based on logic programming principles and rule languages for the Semantic Web based on logic programming are an ongoing discussion. Frame Logic allows object-oriented style (frame-based) modeling in a logical language. RuleML is an XML-based syntax consisting of different sublanguages for the exchange of specifications in different logical languages over the Web.


2010 ◽  
Vol 10 (4-6) ◽  
pp. 547-563 ◽  
Author(s):  
MARTIN SLOTA ◽  
JOÃO LEITE

AbstractThe need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics forhybrid knowledge basescomposed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. These semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve.In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. Then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties.To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.


2014 ◽  
Vol 5 (4) ◽  
pp. 52-76
Author(s):  
Shamim H Ripon ◽  
Sk. Jahir Hossain ◽  
Moshiur Mahamud Piash

Software Product Line (SPL) provides the facility to systematically reuse of software improving the efficiency of software development regarding time, cost and quality. The main idea of SPL is to identify the common core functionality that can be implemented once and reused afterwards. A variant model has also to be developed to manage the variants of the SPL. Usually, a domain model consisting of the common and variant requirements is developed during domain engineering phase to alleviate the reuse opportunity. The authors present a product line model comprising of a variant part for the management of variant and a decision table to depict the customization of decision regarding each variant. Feature diagrams are widely used to model SPL variants. Both feature diagram and our variant model, which is based on tabular method, lacks logically sound formal representation and hence, not amenable to formal verification. Formal representation and verification of SPL has gained much interest in recent years. This chapter presents a logical representation of the variant model by using first order logic. With this representation, the table based variant model as well as the graphical feature diagram can now be verified logically. Besides applying first-order-logic to model the features, the authors also present an approach to model and analyze SPL model by using semantic web approach using OWL-DL. The OWL-DL representation also facilitates the search and maintenance of feature models and support knowledge sharing within a reusable engineering context. Reasoning tools are used to verify the consistency of the feature configuration for both logic-based and semantic web-based approaches.


2009 ◽  
pp. 596-614 ◽  
Author(s):  
I. Koffina ◽  
G. Serfiotis ◽  
V. Christophides ◽  
V. Tannen

Semantic Web (SW) technology aims to facilitate the integration of legacy data sources spread worldwide. Despite the plethora of SW languages (e.g., RDF/S, OWL) recently proposed for supporting large-scale information interoperation, the vast majority of legacy sources still rely on relational databases (RDB) published on the Web or corporate intranets as virtual XML. In this article, we advocate a first-order logic framework for mediating high-level queries to relational and/or XML sources using community ontologies expressed in a SW language such as RDF/S. We describe the architecture and reasoning services of our SW integration middleware, termed SWIM, and we present the main design choices and techniques for supporting powerful mappings between different data models, as well as reformulation and optimization of queries expressed against mediator ontologies and views.


10.29007/22x6 ◽  
2018 ◽  
Author(s):  
Sylvia Grewe ◽  
Sebastian Erdweg ◽  
Mira Mezini

Type systems for programming languages shall detect type errors in programs before runtime. To ensure that a type system meets this requirement, its soundness must be formally verified. We aim at automating soundness proofs of type systems to facilitate the development of sound type systems for domain-specific languages.Soundness proofs for type systems typically require induction. However, many of the proofs of individual induction cases only require first-order reasoning. For the development of our workbench Veritas, we build on this observation by combining automated first-order theorem provers such as Vampire with automated proof strategies specific to type systems. In this paper, we describe how we encode type soundness proofs in first-order logic using TPTP. We show how we use Vampire to prove the soundness of type systems for the simply-typed lambda calculus and for parts of a typed SQL. We report on which parts of the proofs are handled well by Vampire, and what parts work less well with our current approach.


Author(s):  
Donald W. Loveland ◽  
Gopalan Nadathur

A proof procedure is an algorithm (technically, a semi-decision procedure) which identifies a formula as valid (or unsatisfiable) when appropriate, and may not terminate when the formula is invalid (satisfiable). Since a proof procedure concerns a logic the procedure takes a special form, superimposing a search strategy on an inference calculus. We will consider a certain collection of proof procedures in the light of an inference calculus format that abstracts the concept of logic programming. This formulation allows us to look beyond SLD-resolution, the proof procedure that underlies Prolog, to generalizations and extensions that retain an essence of logic programming structure. The inference structure used in the formulation of the logic programming concept and first realization, Prolog, evolved from the work done in the subdiscipline called automated theorem proving. While many proof procedures have been developed within this subdiscipline, some of which appear in Volume 1 of this handbook, we will present a narrow selection, namely the proof procedures which are clearly ancestors of the first proof procedure associated with logic programming, SLD-resolution. Extensive treatment of proof procedures for automated theorem proving appear in Bibel [Bibel, 1982], Chang and Lee [Chang and Lee, 1973] and Loveland [Loveland, 1978]. Although the consideration of proof procedures for automated theorem proving began about 1958 we begin our overview with the introduction of the resolution proof procedure by Robinson in 1965. We then review the linear resolution procedures, model elimination and SL-resolution procedures. Our exclusion of other proof procedures from consideration here is due to our focus, not because other procedures are less important historically or for general use within automated or semi-automated theorem process. After a review of the general resolution proof procedure, we consider the linear refinement for resolution and then further restrict the procedure format to linear input resolution. Here we are no longer capable of treating full first-order logic, but have forced ourselves to address a smaller domain, in essence the renameable Horn clause formulas. By leaving the resolution format, indeed leaving traditional formula representation, we see there exists a linear input procedure for all of first-order logic.


Author(s):  
Grigory Olkhovikov ◽  
Guillermo Badia

Abstract In the style of Lindström’s theorem for classical first-order logic, this article characterizes propositional bi-intuitionistic logic as the maximal (with respect to expressive power) abstract logic satisfying a certain form of compactness, the Tarski union property and preservation under bi-asimulations. Since bi-intuitionistic logic introduces new complexities in the intuitionistic setting by adding the analogue of a backwards looking modality, the present paper constitutes a non-trivial modification of the previous work done by the authors for intuitionistic logic (Badia and Olkhovikov, 2020, Notre Dame Journal of Formal Logic, 61, 11–30).


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