Querying Non-Materialized Ontology Views

One approach to simplifying ontologies, for inclusion in a more tractable semantic web, is through the use of non-materialized view queries. View queries define how a simplified “view” or “application” ontology is derived from larger more complex ontologies. In this work we look at a language for specifying view queries over OWL/RDFS sources, and we illustrate some initial ideas for how to execute user queries over our view ontology, without materializing it first

A Query Integrator and Manager for the Query Web

We introduce two concepts: the Query Web as a layer of interconnected queries over the document web and the semantic web, and a Query Web Integrator and Manager (QI) that enables the Query Web to evolve. QI permits users to write, save and reuse queries over any web accessible source, including other queries saved in other installations of QI. The saved queries may be in any language (e.g. SPARQL, XQuery); the only condition for interconnection is that the queries return their results in some form of XML. This condition allows queries to chain off each other, and to be written in whatever language is appropriate for the task. We illustrate the potential use of QI for several biomedical use cases, including ontology view generation using a combination of graph-based and logical approaches, value set generation for clinical data management, image annotation using terminology obtained from an ontology web service, ontology-driven brain imaging data integration, small-scale clinical data integration, and wider-scale clinical data integration. Such use cases illustrate the current range of applications of QI and lead us to speculate about the potential evolution from smaller groups of interconnected queries into a larger query network that layers over the document and semantic web. The resulting Query Web could greatly aid researchers and others who now have to manually navigate through multiple information sources in order to answer specific questions

Value Sets via Ontology Views

We present a method for defining value sets as queries over ontologies (ontology views), and a mechanism for evaluating such queries. In particular we demonstrate an approach utilizing reusable template queries and parameterized URLs. We illustrate this method using an example from the Ontology of Clinical Research (OCRe)

Ontology View Query Management

Like views in relational databases, ontology views are expressed as queries, but over source ontologies rather than tables. To enhance the reusability of such views, we are constructing a view Query Manager application. The Query Manager allows queries to be edited, executed, and stored for reuse. View queries are discoverable by searching the Query Manager's metadata catalog. The Query Manager also supports the storage of materialized view results upon which further queries may be issued

vSPARQL: A View Definition Language for the Semantic Web

Translational medicine applications would like to leverage the biological and biomedical ontologies, vocabularies, and data sets available on the semantic web. We present a general solution for RDF information set reuse inspired by database views. Our view definition language, vSPARQL, allows applications to specify the exact content that they are interested in and how that content should be restructured or modified. Applications can access relevant content by querying against these view definitions. We evaluate the expressivity of our approach by defining views for practical use cases and comparing our view definition language to existing query languages

Challenges in Reconciling Different Views of Neuroanatomy in a Reference Ontology of Anatomy

A fundamental requirement for integrating neuroscience data is a well-structured ontology that can incorporate, accommodate and reconcile different neuroanatomical views. Here we describe the challenges in creating such ontology, and, because of its principled design, illustrate the potential of the Foundational Model of Anatomy to be that ontology

Distributed Queries for Quality Control Checks in Clinical Trials

Operational Quality Control (QC) checks are standard practice in clinical trials and ensure ongoing compliance with the study protocol, standard operating procedures (SOPs) and Good Clinical Practice (GCP). We present a method for defining QC checks as distributed queries over case report forms (CRF) and clinical imaging data- sources. Our distributed query system can integrate time-sensitive information in order to populate QC checks that can facilitate discrepancy resolution workflow in clinical trials

Emotion Differentiation as a Protective Factor Against Nonsuicidal Self-Injury in Borderline Personality Disorder

Evidence that nonsuicidal self-injury (NSSI) serves a maladaptive emotion regulation function in borderline personality disorder (BPD) has drawn attention to processes that may increase risk for NSSI by exacerbating negative emotion, such as rumination. However, more adaptive forms of emotion processing, including differentiating broad emotional experiences into nuanced emotion categories, might serve as a protective factoragainst NSSI. Using an experience-sampling diary, the present study tested whether differentiation of negative emotion was associated with lower frequency of NSSI acts and urges in 38 individuals with BPD who reported histories of NSSI. Participants completed a dispositional measure of rumination and a 21-day experience-sampling diary, which yielded an index of negative emotion differentiation and frequency of NSSI acts and urges. A significant rumination by negative emotion differentiation interaction revealed that rumination predicted higher rates of NSSI acts and urges in participants with difficulty differentiating their negative emotions. The results extend research on emotion differentiation into the clinical literature and provide empirical support for clinical theories that suggest emotion identification and labeling underlie strategies for adaptive self-regulation and decreased NSSI risk in BPD

Practical learning method for multi-scale entangled states

We describe a method for reconstructing multi-scale entangled states from a small number of efficiently-implementable measurements and fast post-processing. The method only requires single particle measurements and the total number of measurements is polynomial in the number of particles. Data post-processing for state reconstruction uses standard tools, namely matrix diagonalisation and conjugate gradient method, and scales polynomially with the number of particles. Our method prevents the build-up of errors from both numerical and experimental imperfections

Enabling RadLex with the Foundational Model of Anatomy Ontology to Organize and Integrate Neuro-imaging Data

In this study we focused on empowering RadLex with an ontological framework and additional content derived from the Foundational Model of Anatomy Ontology1 thereby providing RadLex the facility to correlate the different standards used in annotating neuroradiological image data. The objective of this work is to promote data sharing, data harmonization and interoperability between disparate neuroradiological labeling systems