Reasoning by analogy in the generation of domain acceptable ontology refinements

Refinements generated for a knowledge base often involve the learning of new knowledge to be added to or replace existing parts of a knowledge base. However, the justifiability of the refinement in the context of the domain (domain acceptability) is often overlooked. The work reported in this paper describes an approach to the generation of domain acceptable refinements for incomplete and incorrect ontology individuals through reasoning by analogy using existing domain knowledge. To illustrate this approach, individuals for refinement are identified during the application of a knowledge-based system, EIRA; when EIRA fails in its task, areas of its domain ontology are identified as requiring refinement. Refinements are subsequently generated by identifying and reasoning with similar individuals from the domain ontology. To evaluate this approach EIRA has been applied to the Intensive Care Unit (ICU) domain. An evaluation (by a domain expert) of the refinements generated by EIRA has indicated that this approach successfully produces domain acceptable refinements

Benchmarking the RDF(S) interoperability of ontology tools

The number of ontology tools, such as ontology editors and repositories, is constantly rising. Ideally, one could use them all seamlessly and thus benefit from all the functionalities they offer. As shown in previous EON workshops, interoperability among different development tools is not straightforward since ontology editors rely on specific internal knowledge models which are translated into common formats such as RDF(S). This paper addresses the urgent need for interoperability by providing an exhaustive set of RDF(S) benchmarks and demonstrating in an extensive field study the state-of-the-art of interoperability among six ontology tools. From the field study we have compiled a comprehensive set of best practices which may serve as guidelines. Tool developers benefit from having guidelines to design their import and export functionalities and a concrete set of benchmarks against which they can evaluate their import and export functionalities. Ontology engineers benefit from our work by having an overview to which extend interoperability is ensured for combinations of specific tools

An Infrastructure for acquiring high quality semantic metadata

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a erification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation omparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata

Science Models as Value-Added Services for Scholarly Information Systems

The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.Comment: 26 pages, to appear in Scientometric

Effectiveness of Lumbar Cerebrospinal Fluid Drain Among Patients With Aneurysmal Subarachnoid Hemorrhage: A Randomized Clinical Trial.

IMPORTANCE After aneurysmal subarachnoid hemorrhage, the use of lumbar drains has been suggested to decrease the incidence of delayed cerebral ischemia and improve long-term outcome. OBJECTIVE To determine the effectiveness of early lumbar cerebrospinal fluid drainage added to standard of care in patients after aneurysmal subarachnoid hemorrhage. DESIGN, SETTING, AND PARTICIPANTS The EARLYDRAIN trial was a pragmatic, multicenter, parallel-group, open-label randomized clinical trial with blinded end point evaluation conducted at 19 centers in Germany, Switzerland, and Canada. The first patient entered January 31, 2011, and the last on January 24, 2016, after 307 randomizations. Follow-up was completed July 2016. Query and retrieval of data on missing items in the case report forms was completed in September 2020. A total of 20 randomizations were invalid, the main reason being lack of informed consent. No participants meeting all inclusion and exclusion criteria were excluded from the intention-to-treat analysis. Exclusion of patients was only performed in per-protocol sensitivity analysis. A total of 287 adult patients with acute aneurysmal subarachnoid hemorrhage of all clinical grades were analyzable. Aneurysm treatment with clipping or coiling was performed within 48 hours. INTERVENTION A total of 144 patients were randomized to receive an additional lumbar drain after aneurysm treatment and 143 patients to standard of care only. Early lumbar drainage with 5 mL per hour was started within 72 hours of the subarachnoid hemorrhage. MAIN OUTCOMES AND MEASURES Primary outcome was the rate of unfavorable outcome, defined as modified Rankin Scale score of 3 to 6 (range, 0 to 6), obtained by masked assessors 6 months after hemorrhage. RESULTS Of 287 included patients, 197 (68.6%) were female, and the median (IQR) age was 55 (48-63) years. Lumbar drainage started at a median (IQR) of day 2 (1-2) after aneurysmal subarachnoid hemorrhage. At 6 months, 47 patients (32.6%) in the lumbar drain group and 64 patients (44.8%) in the standard of care group had an unfavorable neurological outcome (risk ratio, 0.73; 95% CI, 0.52 to 0.98; absolute risk difference, -0.12; 95% CI, -0.23 to -0.01; P = .04). Patients treated with a lumbar drain had fewer secondary infarctions at discharge (41 patients [28.5%] vs 57 patients [39.9%]; risk ratio, 0.71; 95% CI, 0.49 to 0.99; absolute risk difference, -0.11; 95% CI, -0.22 to 0; P = .04). CONCLUSION AND RELEVANCE In this trial, prophylactic lumbar drainage after aneurysmal subarachnoid hemorrhage lessened the burden of secondary infarction and decreased the rate of unfavorable outcome at 6 months. These findings support the use of lumbar drains after aneurysmal subarachnoid hemorrhage. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01258257

The molecular pathology of p53 in primitive neuroectodermal tumours of the central nervous system

One hundred and one pre-treatment primary central primitive neuroectodermal tumours were analysed for the expression of p53 protein by immunohistochemistry using the monoclonal antibody DO-7. The staining intensity was classified into four groups: strong, medium, weak and negative and strong staining intensity was associated with the poorest survival. DNA sequencing of the p53 gene was performed in 28 cases representing all four staining groups. Mutations were found in only three of the strong staining tumours suggesting that DNA mutations were not common events and that in the majority of the tumours with over-expressed p53, the protein was likely to be wild-type. Results of immunohistochemistry showed a significantly positive relationship between the expression of p53 and Bax and Bcl-2 proteins, but not Waf-1. Multivariate analyses supported the prognostic value of p53 immunostaining in central primitive neuroectodermal tumours and also of age and gender of patients

Developing Ontologies withing Decentralized Settings

This chapter addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This chapter presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralised settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering

Benchmarking Ontologies: Bigger or Better?

A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1) four of the most common medical ontologies with respect to a corpus of medical documents and (2) seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them