Completeness based classification algorithm: a novel approach for educational semantic data completeness assessment

Purpose The purpose of this paper is to reveal the smart collaborative learning service. This concept aims to build teams of learners based on the complementarity of their skills, allowing flexible participation and offering interdisciplinary collaboration opportunities for all the learners. The success of this environment is related to predict efficient collaboration between the different teammates, allowing a smartly sharing knowledge in the Smart University environment. Design/methodology/approach A random forest (RF) approach is proposed, which is based on semantic modelization of the learner and the problem-solving allowing multidisciplinary collaboration, and heuristic completeness processing to build complementary teams. To achieve that, this paper established a Konstanz Information Miner workflow that integrates the main steps for building and evaluating the RF classifier, this workflow is divided into: extracting knowledge from the smart collaborative learning ontology, calculating the completeness using a novel heuristic and building the RF classifier. Findings The smart collaborative learning service enables efficient collaboration and democratized sharing of knowledge between learners, by using a semantic support decision support system. This service solves a frequent issue related to the composition of learning groups to serve pedagogical perspectives. Originality/value The present study harmonizes the integration of ontology, a new heuristic processing and supervised machine learning algorithm aiming at building an intelligent collaborative learning service that includes a qualified classifier of complementary teams of learners.

Practical guide for obtaining and validating chromosome-scale genome assemblies with Hi-C scaffolding

Recent development of ecological studies has been fueled by the introduction of massive information based on chromosome-scale genome sequences, even for species whose genetic linkage was previously not accessible. This was enabled mainly by the application of Hi-C, a method for genome-wide chromosome conformation capture which was originally developed for investigating long-range interaction of chromatins. Performing genomic scaffolding using Hi-C data is highly resource-demanding in elaborate laboratory steps for sequencing sample preparation, building primary genome sequence assembly as an input, and computation for genome scaffolding using Hi-C data, followed by careful validation. This article summarizes existing solutions for these steps and provides a test case of its application to a reptile species, the Madagascar ground gecko (Paroedura picta). Among frequently exerted metrics for evaluating scaffolding results, we investigate the validity of completeness assessment using single-copy reference orthologs and report problems with the widely used program pipeline BUSCO.

Completeness Check of Experimental Fission Product Yield Data in EXFOR Database

The IAEA conducted the completeness assessment of fission product yield (FPY) data in EXFOR database against two bibliographies that were used in ENDF/B-VI and UKFY3.0 library evaluations. We found that 194 articles are found to be relevant for new entry.

Real-world data in retinal diseases treated with anti-vascular endothelial growth factor (anti-VEGF) therapy – a systematic approach to identify and characterize data sources

Background Real-world data (RWD) has been a valuable addition to the scientific literature regarding treatment pathways, clinical outcomes and characteristics of patients with retinal diseases in recent years. Registries, observational studies and patient databases are often used for real-world research. However, there is limited information for each data source on the design, consistency, data captured, limitations and usability for assessing research questions. Using a systematic approach, we identified RWD sources for patients with retinal diseases and assessed them for completeness of data relating to different outcomes. Methods A systematic literature review was carried out to identify RWD sources for patients with retinal disease. Potentially relevant articles published between 2006 and 2016 were screened following electronic searches in Embase and MEDLINE. Congress and supplementary searches were undertaken to identify RWD sources that may not be referenced in full publications. For each data source, availability and quantity of data on baseline status, clinical outcomes, treatment and management, safety, and patient-reported and economic burden were assessed using a bespoke completeness assessment tool based on International Consortium for Health Outcomes Measurement guidelines for macular degeneration. Completeness of data for each area of interest in each data source was assessed and rated using a ‘good–moderate–poor’ rating system based on availability and quantity of available data. Each data source was then given an overall score based on its score for each of the 7 areas of interest. Results A total of 128 RWD sources from 32 countries were identified. Of the identified sources, 64 sources from 16 countries of interest were analyzed. Most of these sources provided information on baseline status and clinical outcomes and treatment, but few collected data on economic and patient-reported burden. Of the RWD sources analyzed, 10 scored highly in the overall completeness assessment, collecting data on most or all of the areas of interest; these sources are considered to be robust data sources for performing ophthalmology real-world studies. Conclusions The study provides a comprehensive list of RWD sources for patients with retinal disease, many of which will be useful for conducting real-world studies in the field of ophthalmology.