There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

1 Why develop an ontology? In recent years the development of ontologies—explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)—has been moving from the realm of ArtificialIntelligence laboratories to the desktops of domain experts. Ontologies have become common on the World-Wide Web. The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com). The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000). Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as SNOMED (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993). Broad general-purpose ontologies are emerging as well. For example, the United Nations Development Program and Dun & Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services (www.unspsc.org). An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. Why would someone want to develop an ontology? Some of the reasons are:

/pdf/ontology-development-101-a-guide-to-creating-your-first-2c6x0j449d.pdf

Ontology Development 101: A Guide to Creating Your First Ontology

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.

/pdf/yago-a-core-of-semantic-knowledge-13k3nmj6l2.pdf

Yago: a core of semantic knowledge

Ontologies have recently became a popular mechanism to expose relational database RDBs due to their ability to describe the domain of data in terms of classes and properties that are clear to domain experts. Ontological terms are related to the schema of the underlying databases with the help of mappings, i.e., declarative specifications associating SQL queries to ontological terms. Developing appropriate ontologies and mappings for given RDBs is a challenging and time consuming task. In this work we present BootOX, a system that aims at facilitating ontology and mapping development by their automatic extraction i.e., bootstrapping from RDBs, and our experience with the use of BootOX in industrial and research contexts. BootOX has a number of advantages: it allows to control the OWL 2 profile of the output ontologies, bootstrap complex and provenance mappings, which are beyond the W3C direct mapping specification. Moreover, BootOX allows to import pre-existing ontologies via alignment.

/pdf/bootox-practical-mapping-of-rdbs-to-owl-2-dhd8jvfow0.pdf

BootOX: Practical Mapping of RDBs to OWL 2

Currently computers are changing from single isolated devices to entry points into a worldwide network of information exchange and business transactions called the World Wide Web (WWW). Therefore support in the exchange of data, information, and knowledge is becoming the key issue in current computer technology. Ontologies provide a shared and common understanding of a domain that can be communicated between people and application systems. Therefore, they may play a major role in supporting information exchange processes in various areas. However, in order to develop their full power, the representation languages for ontologies must be applicable to existing data exchange standards in the World Wide Web. Therefore, we will compare ontology representation languages with document structure techniques (schemata) on the web. We will do this by giving a detailed comparison of OIL, a proposal for expressing ontologies in the Web, with XML Schema, a proposed standard for describing the structure and semantics of Web documents. We will argue that these two refer to different levels of abstraction and illustrate this claim by providing an translation procedure from the first to the latter.123

/pdf/the-relation-between-ontologies-and-xml-schemas-13akqzmgs6.pdf

The relation between ontologies and XML schemas

Classification is a fundamental reasoning task in ontology design, and there is currently a wide range of reasoners highly optimised for classification of OWL 2 ontologies. There are also several reasoners that are complete for restricted fragments of OWL 2 , such as the OWL 2 EL profile. These reasoners are much more efficient than fully-fledged OWL 2 reasoners, but they are not complete for ontologies containing (even if just a few) axioms outside the relevant fragment. In this paper, we propose a novel classification technique that combines an OWL 2 reasoner and an efficient reasoner for a given fragment in such a way that the bulk of the workload is assigned to the latter. Reasoners are combined in a black-box modular manner, and the specifics of their implementation (and even of their reasoning technique) are irrelevant to our approach.

/pdf/more-modular-combination-of-owl-reasoners-for-ontology-3cocha8cbt.pdf

MORe: modular combination of OWL reasoners for ontology classification

Although the combination of OWL and Horn rules results in the creation of a highly expressive language, i.e. SWRL, there are still many occasions where this language fails to accurately represent knowledge of our world. In particular, SWRL fails at representing vague and imprecise knowledge and information. Such type of information is apparent in many applications like multimedia processing and retrieval, information fusion, etc. In this paper, we propose f-SWRL, a fuzzy extension to SWRL to include fuzzy assertions (such as ‘Mary is tall in the degree of 0.9') and fuzzy rules (such as ‘being healthy is more important than being rich to determine if one is happy').

/pdf/f-swrl-a-fuzzy-extension-of-swrl-1ithrjlt66.pdf

f-SWRL: a fuzzy extension of SWRL

Answering conjunctive queries (CQs) over a set of facts extended with existential rules is a prominent problem in knowledge representation and databases. This problem can be solved using the chase algorithm, which extends the given set of facts with fresh facts in order to satisfy the rules. If the chase terminates, then CQs can be evaluated directly in the resulting set of facts. The chase, however, does not terminate necessarily, and checking whether the chase terminates on a given set of rules and facts is undecidable. Numerous acyclicity notions were proposed as sufficient conditions for chase termination. In this paper, we present two new acyclicity notions called model-faithful acyclicity (MFA) and model-summarising acyclicity (MSA). Furthermore, we investigate the landscape of the known acyclicity notions and establish a complete taxonomy of all notions known to us. Finally, we show that MFA and MSA generalise most of these notions. 
Existential rules are closely related to the Horn fragments of the OWL 2 ontology language; furthermore, several prominent OWL 2 reasoners implement CQ answering by using the chase to materialise all relevant facts. In order to avoid termination problems, many of these systems handle only the OWL 2 RL profile of OWL 2; furthermore, some systems go beyond OWL 2 RL, but without any termination guarantees. In this paper we also investigate whether various acyclicity notions can provide a principled and practical solution to these problems. On the theoretical side, we show that query answering for acyclic ontologies is of lower complexity than for general ontologies. On the practical side, we show that many of the commonly used OWL 2 ontologies are MSA, and that the number of facts obtained by materialisation is not too large. Our results thus suggest that principled development of materialisation-based OWL 2 reasoners is practically feasible.

/pdf/acyclicity-notions-for-existential-rules-and-their-5abiouaszw.pdf

Ian Horrocks

Papers

BootOX: Practical Mapping of RDBs to OWL 2

The relation between ontologies and XML schemas

MORe: modular combination of OWL reasoners for ontology classification

f-SWRL: a fuzzy extension of SWRL

Acyclicity Notions for Existential Rules and Their Application to Query Answering in Ontologies