The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real world instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. We present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.
The ScholOnto ontology was developed as part of an effort aimed at enabling researchers to describe and debate, via a semantic network, the contributions of a document, and its relationship to the literature @cite_4 . While this ontology supports the concept of a scholarly document and a scholarly agent, it focuses on formally summarizing and interactively debating claims made in documents, not on expressing the actual use of documents. Moreover, support for bibliographic data is minimal whereas support for discourse constructs, not required for MESUR, is very detailed.
@cite_4
2130307546 2610389136 2069206951 2133999934
The internet is rapidly becoming the first place for researchers to publish documents, but at present they receive little support in searching, tracking, analysing or debating concepts in a literature from scholarly perspectives. This paper describes the design rationale and implementation of ScholOnto, an ontology-based digital library server to support scholarly interpretation and discourse. It enables researchers to describe and debate via a semantic network the contributions a document makes, and its relationship to the literature. The paper discusses the computational services that an ontology-based server supports, alternative user interfaces to support interaction with a large semantic network, usability issues associated with knowledge formalisation, new work practices that could emerge, and related work. Ontology evolution is an important problem in the Semantic Web research. Recently, Alchourron, Gardenfors and Markinson's (AGM) theory on belief change has been applied to deal with this problem. However, most of current work only focuses on the feasibility of the application of AGM postulates on contraction to description logics (DLs), a family of ontology languages. So the explicit construction of a revision operator is ignored. In this paper, we first generalize the AGM postulates on revision to DLs. We then define two revision operators in DLs. One is the weakening-based revision operator which is defined by weakening of statements in a DL knowledge base and the other is its refinement. We show that both operators capture some notions of minimal change and satisfy the generalized AGM postulates for revision. Abstract: In this paper we motivate why it is crucial to associate linguistic information with ontologies and why more expressive models, beyond the label systems implemented in RDF, OWL and SKOS, are needed to capture the relation between natural language constructs and ontological structures. We argue that in the light of tasks such as ontology-based information extraction (i.e., ontology population) from text, ontology learning from text, knowledge-based question answering and ontology verbalization, currently available models do not suffice as they only allow us to associate literals as labels to ontology elements. Using literals as labels, however, does not allow us to capture additional linguistic structure or information which is definitely needed as we argue. In this paper we thus present a model for linguistic grounding of ontologies called LexInfo. LexInfo allows us to associate linguistic information to elements in an ontology with respect to any level of linguistic description and expressivity. LexInfo has been implemented as an OWL ontology and is freely available together with an API. Our main contribution is the model itself, but even more importantly a clear motivation why more elaborate models for associating linguistic information with ontologies are needed. We also further discuss the implementation of the LexInfo API, different tools that support the creation of LexInfo lexicons as well as some preliminary applications. The SWAT Tools ontology verbaliser generates a hierarchically organised hypertext designed for easy comprehension and navigation. The document structure, inspired by encyclopedias and glossaries, is organised at a number of levels. At the top level, a heading is generated for every concept in the ontology; at the next level, each entry is subdivided into logically-based headings like 'Definition' and 'Examples'; at the next, sentences are aggregated when they have parts in common; at the lowest level, phrases are hyperlinked to concept headings. One consequence of this organisation is that some statements are repeated because they are relevant to more than one entry; this means that the text is longer than one in which statements are simply listed. This trade-off between organisation and brevity is investigated in a user study.