An Information Extraction Approach to Reorganizing and Summarizing Specifications

Materials and Process Specifications are complex semi-structured documents containing numeric data, text, and images. This article describes a coarse-grain extraction technique to automatically reorganize and summarize spec content. Specifically, a strategy for semantic-markup, to capture content within a semantic ontology, relevant to semi-automatic extraction, has been developed and experimented with. The working prototypes were built in the context of Cohesia\u27s existing software infrastructure, and use techniques from Information Extraction, XML technology, etc

Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility

peer reviewe

Semi-Automatic Content Extraction from Specifications

Specifications are critical to companies involved in complex manufacturing. The constant reading, reviewing, and analysis of materials and process specifications is extremely labor-intensive, quality impacting, and time-consuming. A conceptual design for a tool that provides computer-assistance in the interpretation of specification requirements has been created and a strategy for semantic-markup, which is the overlaying of abstract syntax (“the essence”) on the text, has been developed. The solution is based on the techniques for Information Extraction and the XML technology, and it captures the specification content within a semantic ontology. The working prototype of the tool being built will serve as the foundation for potential full-scale commercialization

An Information Extraction Approach to Reorganizing and Summarizing Specifications

Materials and Process Specifications are complex semi-structured documents containing numeric data, text, and images. This article describes a coarse-grain extraction technique to automatically reorganize and summarize spec content. Specifically, a strategy for semantic-markup, to capture content within a semantic ontology, relevant to semi-automatic extraction, has been developed and experimented with. The working prototypes were built in the context of Cohesia\u27s existing software infrastructure, and use techniques from Information Extraction, XML technology, etc

Semi-Automatic Content Extraction from Specifications

Specifications are critical to companies involved in complex manufacturing. The constant reading, reviewing, and analysis of materials and process specifications is extremely labor-intensive, quality impacting, and time-consuming. A conceptual design for a tool that provides computer-assistance in the interpretation of specification requirements has been created and a strategy for semantic-markup, which is the overlaying of abstract syntax (“the essence”) on the text, has been developed. The solution is based on the techniques for Information Extraction and the XML technology, and it captures the specification content within a semantic ontology. The working prototype of the tool being built will serve as the foundation for potential full-scale commercialization

Reporting guidelines for human microbiome research: the STORMS checklist

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results. The STORMS tool provides guidance for concise and complete reporting of microbiome studies to facilitate manuscript preparation, peer review, reader comprehension of publications, and comparative analysis of published results