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The Journal of Urology Jun 2020
Topics: Cytoreduction Surgical Procedures; Data Management; Humans; Kidney; Kidney Neoplasms; Registries
PubMed: 32208967
DOI: 10.1097/JU.0000000000000741.01 -
Studies in Health Technology and... May 2021Intraoperative neurophysiological monitoring (IOM) enables a function-preserving surgical strategy for surgeries of brain or spinal cord pathologies by...
Intraoperative neurophysiological monitoring (IOM) enables a function-preserving surgical strategy for surgeries of brain or spinal cord pathologies by neurophysiological measurements. However, the IOM data management at neurosurgical institutions are often either not digitized or inefficient in terms of collecting, storing and processing of IOM data. Here, we describe the development of a web application, called IOM-Manager, as a first step towards the complete digitization of the IOM workflow. The web application is used for structured protocoling based on standardized protocol entry catalog, data archiving, and data analysis. These functionalities are based on the results of the requirement engineering of a process analysis, a survey with potential users and a market analysis. A usability test with one IOM team indicated the IOM-Manager and its other components can in fact solve many problems of existing solutions.
Topics: Data Management; Evoked Potentials, Somatosensory; Intraoperative Neurophysiological Monitoring; Neurophysiology; Neurosurgical Procedures
PubMed: 34042896
DOI: 10.3233/SHTI210071 -
Methods in Molecular Biology (Clifton,... 2022With the evermore emphasis put on open science and its invaluable benefits to the scientific community, it is no longer the case where a research project simply ends...
With the evermore emphasis put on open science and its invaluable benefits to the scientific community, it is no longer the case where a research project simply ends with a scientific publication. The benefits of data sharing and reproducibility of results have taken the centerpiece within the life science research supported by FAIR principles that firmly underline the importance of open data. The current data-intensive multidisciplinary research has also highlighted the significance of how data is mined and managed. Here we describe some of the features adopted by EMBL-EBI data resources to support data mining, data quality, and data management. We also highlight how EMBL-EBI has responded to the current pandemic through its data resources.
Topics: Biological Science Disciplines; Data Management; Data Mining; Information Dissemination; Reproducibility of Results
PubMed: 35507257
DOI: 10.1007/978-1-0716-2095-3_1 -
Database : the Journal of Biological... Sep 2022The rapid advancement of sequencing technology, including next-generation sequencing (NGS), has greatly improved sequencing efficiency and decreased cost. Consequently,...
The rapid advancement of sequencing technology, including next-generation sequencing (NGS), has greatly improved sequencing efficiency and decreased cost. Consequently, huge amounts of genomic, transcriptomic and epigenetic data concerning cotton species have been generated and released. These large-scale data provide immense opportunities for the study of cotton genomic structure and evolution, population genetic diversity and genome-wide mining of excellent genes for important traits. However, the complexity of NGS data also causes distress, as it cannot be utilized easily. Here, we presented the cotton omics data platform COTTONOMICS (http://cotton.zju.edu.cn/), an easily accessible web database that integrates 32.5 TB of omics data including seven assembled genomes, resequencing data from 1180 allotetraploid cotton accessions and RNA-sequencing (RNA-seq), small RNA-sequencing (smRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), DNase hypersensitive sites sequencing (DNase-seq) and Bisulfite sequencing (BS-seq). COTTONOMICS allows users to employ various search scenarios and retrieve information concerning the cotton genomes, genomic variation (Single nucleotide polymorphisms (SNPs) and Insertion and Deletion (InDels)), gene expression, smRNA expression, epigenetic regulation and quantitative trait locus (QTLs). The user-friendly web interface offers a variety of modules for storing, retrieving, analyzing and visualizing cotton multi-omics data to diverse ends, thereby enabling users to decipher cotton population genetics and identify potential novel genes that influence agronomically beneficial traits. Database URL: http://cotton.zju.edu.cn.
Topics: Data Management; Deoxyribonucleases; Epigenesis, Genetic; High-Throughput Nucleotide Sequencing; RNA
PubMed: 36094905
DOI: 10.1093/database/baac080 -
GigaScience Dec 2022Scientists employing omics in life science studies face challenges such as the modeling of multiassay studies, recording of all relevant parameters, and managing many...
Scientists employing omics in life science studies face challenges such as the modeling of multiassay studies, recording of all relevant parameters, and managing many samples with their metadata. They must manage many large files that are the results of the assays or subsequent computation. Users with diverse backgrounds, ranging from computational scientists to wet-lab scientists, have dissimilar needs when it comes to data access, with programmatic interfaces being favored by the former and graphical ones by the latter. We introduce SODAR, the system for omics data access and retrieval. SODAR is a software package that addresses these challenges by providing a web-based graphical user interface for managing multiassay studies and describing them using the ISA (Investigation, Study, Assay) data model and the ISA-Tab file format. Data storage is handled using the iRODS data management system, which handles large quantities of files and substantial amounts of data. SODAR also offers programmable APIs and command-line access for metadata and file storage. SODAR supports complex omics integration studies and can be easily installed. The software is written in Python 3 and freely available at https://github.com/bihealth/sodar-server under the MIT license.
Topics: Multiomics; Metadata; Software; Information Storage and Retrieval; Data Management
PubMed: 37498129
DOI: 10.1093/gigascience/giad052 -
The Surgical Clinics of North America Apr 2023Big Data is transforming health care. Characteristics of Big Data require data management strategies to effectively use, analyze, and apply the data. Clinicians are not... (Review)
Review
Big Data is transforming health care. Characteristics of Big Data require data management strategies to effectively use, analyze, and apply the data. Clinicians are not typically learned in the fundamentals of these strategies which may cause a divide between collected data and data used. This article introduces the fundamentals of Big Data management and encourages clinicians to work with their information technology partners to further understand these processes and to identify opportunities for collaboration.
Topics: Humans; Big Data; Data Management; Databases, Factual; Data Collection; Physicians
PubMed: 36948722
DOI: 10.1016/j.suc.2022.11.007 -
Medical Reference Services Quarterly 2023As the largest public funder of biomedical research in the world, the National Institutes of Health's (NIH) new Data Management and Sharing (DMS) Policy is a large step...
As the largest public funder of biomedical research in the world, the National Institutes of Health's (NIH) new Data Management and Sharing (DMS) Policy is a large step toward shifting the culture of medical research toward a broader sharing of scientific data. Librarians in the health sciences support researchers by assisting with data management plans, research dissemination, abiding by publisher/grant requirements on data sharing, and suggesting recommended repositories for data preservation. This article will serve as a primer on open data, data sharing, the NIH's DMS Policy and its implications, and how librarians can support researchers in this landscape.
Topics: United States; Humans; Data Management; Biomedical Research; Information Dissemination; Librarians; Policy
PubMed: 36862609
DOI: 10.1080/02763869.2023.2168103 -
Scientific Data Jun 2024The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in...
The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data.
Topics: Biomedical Research; Data Management; Information Dissemination
PubMed: 38871749
DOI: 10.1038/s41597-024-03449-z -
Cardiac Electrophysiology Clinics Sep 2021Movement of information from a cardiac implantable electronic device to an electronic health record (EHR) can be a complex and multistep process. It requires unambiguous... (Review)
Review
Movement of information from a cardiac implantable electronic device to an electronic health record (EHR) can be a complex and multistep process. It requires unambiguous patient identification, device identification, standardized semantic and syntactic data nomenclature, common secure data transfer methodology, and structured reporting within the EHR. Common workflow using a commonly accepted methodology, such as the implantable device cardiac observation profile or protocol, is mandatory. Once information reaches the EHR, a uniform report structure appropriate for the consumer (physician or patient) is needed. Often there may be separate reports for each consumer class. Finally, patient acceptance and consent are required.
Topics: Data Management; Electronic Health Records; Humans
PubMed: 34330374
DOI: 10.1016/j.ccep.2021.05.001 -
Studies in Health Technology and... Nov 2021The One Digital Health framework aims at transforming future health ecosystems and guiding the implementation of a digital technologies-based systemic approach to caring...
The One Digital Health framework aims at transforming future health ecosystems and guiding the implementation of a digital technologies-based systemic approach to caring for humans' and animals' health in a managed surrounding environment. To integrate and to use the data generated by the ODH data sources, "FAIRness" stands as a prerequisite for proper data management and stewardship.
Topics: Animals; Data Management; Ecosystem; Humans
PubMed: 34795080
DOI: 10.3233/SHTI210812