Center of Excellence in Research Reporting in Neurosurgery - Diagnostic Ontology

Motivation: Evidence-based medicine (EBM), in the field of neurosurgery, relies on diagnostic studies since Randomized Controlled Trials (RCTs) are uncommon. However, diagnostic study reporting is less standardized which increases the difficulty in reliably aggregating results. Although there have been several initiatives to standardize reporting, they have shown to be sub-optimal. Additionally, there is no central repository for storing and retrieving related articles. Results: In our approach we formulate a computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct Systematic Reviews - Meta Analysis (SR-MA) for diagnostic studies, which will assist in standardized reporting of diagnostic articles. SR-MA are studies that aggregate several studies to come to one conclusion for a particular research question. We also report high percentage of agreement among five observers as a result of the interobserver agreement test that we conducted among them to annotate 13 articles using the diagnostic ontology. Moreover, we extend our existing repository CERR-N to include diagnostic studies. Availability: The ontology is available for download as an.owl file at: http://bioportal.bioontology.org/ontologies/3013

I18n of Semantic Web Applications

Abstract. Recently, the use of semantic technologies has gained quite some traction. With increased use of these technologies, their maturation not only in terms of performance, robustness but also with regard to support of non-latin-based languages and regional differences is of paramount importance. In this paper, we provide a comprehensive review of the current state of the internationalization (I18n) of Semantic Web technologies. Since resource identifiers play a crucial role for the Semantic Web, the internatinalization of resource identifiers is of high importance. It turns out that the prevalent resource identification mechanism on the Semantic Web, i.e. URIs, are not sufficient for an efficient internationalization of knowledge bases. Fortunately, with IRIs a standard for international resource identifiers is available, but its support needs much more penetration and homogenization in various semantic web technology stacks. In addition, we review various RDF serializations with regard to their support for internationalized knowledge bases. The paper also contains an in-depth review of popular semantic web tools and APIs with regard to their support for internationalization.

A model for capturing provenance of assertions about chemical substances

Chemical substance resources on the Web are often made accessible to researchers through public APIs (Application Programming Interfaces). A significant problem of missing provenance information arises when extracting and integrating data in such APIs. Even when provenance is stated, it is usually not done with any prescribed templates or terminology. This creates a burden on data producers and makes it challenging for API developers to automatically extract and analyse this information. Downstream, these consequences hinder efforts to automatically determine the veracity and quality of extracted data, critical for proving the integrity of associated research findings. In this paper, we propose a model for capturing provenance of assertions about chemical substances by systematically analyzing three sources: (i) Nanopublications, (ii) Wikidata and (iii) selected Minimal Information Standards (MISTS) for reporting biomedical studies. We analyse provenance terms used in these sources along with their frequency of use and synthesize our findings into a preliminary model for capturing provenance

Formalizing drug indications on the road to therapeutic intent.

Therapeutic intent, the reason behind the choice of a therapy and the context in which a given approach should be used, is an important aspect of medical practice. There are unmet needs with respect to current electronic mapping of drug indications. For example, the active ingredient sildenafil has 2 distinct indications, which differ solely on dosage strength. In progressing toward a practice of precision medicine, there is a need to capture and structure therapeutic intent for computational reuse, thus enabling more sophisticated decision-support tools and a possible mechanism for computer-aided drug repurposing. The indications for drugs, such as those expressed in the Structured Product Labels approved by the US Food and Drug Administration, appears to be a tractable area for developing an application ontology of therapeutic intent