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Angewandte Chemie (International Ed. in... Aug 2023This invited Team Profile was created by a group of scientists working on concepts for research data management in catalysis in the Department of Inorganic Chemistry at...
This invited Team Profile was created by a group of scientists working on concepts for research data management in catalysis in the Department of Inorganic Chemistry at the Fritz-Haber-Institut (FHI) der Max-Planck-Gesellschaft in Berlin. They recently published an article about their views on the ongoing digital transformation in catalysis research, in which the structure and current status of catalysis data are analyzed to highlight the benefits of FAIR data. Considering the fundamental aspects of catalysis as a kinetic phenomenon, they discuss how working methods should change to achieve a deeper understanding of the physical principles governing catalysis and discover new catalysts. "Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use", C. P. Marshall, J. Schumann, A. Trunschke, Angew. Chem. Int. Ed. Engl. 2023, 62, e202302971.
PubMed: 37427719
DOI: 10.1002/anie.202308495 -
Sensors (Basel, Switzerland) Jan 2024Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad... (Review)
Review
Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing.
PubMed: 38257526
DOI: 10.3390/s24020433 -
Journal of Pancreatology Mar 2024The "omics" revolution has transformed the biomedical research landscape by equipping scientists with the ability to interrogate complex biological phenomenon and... (Review)
Review
The "omics" revolution has transformed the biomedical research landscape by equipping scientists with the ability to interrogate complex biological phenomenon and disease processes at an unprecedented level. The volume of "big" data generated by the different omics studies such as genomics, transcriptomics, proteomics, and metabolomics has led to the concurrent development of computational tools to enable in silico analysis and aid data deconvolution. Considering the intensive resources and high costs required to generate and analyze big data, there has been centralized, collaborative efforts to make the data and analysis tools freely available as "Open Source," to benefit the wider research community. Pancreatology research studies have contributed to this "big data rush" and have additionally benefitted from utilizing the open source data as evidenced by the increasing number of new research findings and publications that stem from such data. In this review, we briefly introduce the evolution of open source omics data, data types, the "FAIR" guiding principles for data management and reuse, and centralized platforms that enable free and fair data accessibility, availability, and provide tools for omics data analysis. We illustrate, through the case study of our own experience in mining pancreatitis omics data, the power of repurposing open source data to answer translationally relevant questions in pancreas research.
PubMed: 38524857
DOI: 10.1097/JP9.0000000000000173 -
Cureus Apr 2024The efficacy of immunization programs is critically dependent on robust supply chain management, a complex challenge exacerbated by expanding program scopes and evolving... (Review)
Review
The efficacy of immunization programs is critically dependent on robust supply chain management, a complex challenge exacerbated by expanding program scopes and evolving vaccine technologies. This comprehensive review underscores the pivotal role of Resource Centers in fortifying the immunization supply chain, presenting a paradigm shift toward enhanced national and global health outcomes. Through a detailed examination of their key activities, the article elucidates how these centers catalyze improvements across various facets of supply chain management - from the integration of suitable technology technologies and specialized training programs to the development of sustainable models and advocacy for policy prioritization. This further explores the multifaceted challenges these centers confront, including funding constraints, capacity building, and infrastructural gaps, alongside the burgeoning opportunities presented by new vaccine introductions, donor interest in health system strengthening, and the potential for broadened scope beyond immunization. By weaving together examples of existing centers worldwide, the review highlights their contributions towards optimizing vaccine logistics, enhancing data management, and ultimately achieving Sustainable Development Goal 3. The insights provided offer valuable guidance for planning and sustaining resource centers, positioning them as indispensable allies in the global pursuit of universal immunization coverage.
PubMed: 38800200
DOI: 10.7759/cureus.58966 -
BMC Bioinformatics Jan 2024The increasing volume and complexity of genomic data pose significant challenges for effective data management and reuse. Public genomic data often undergo similar...
BACKGROUND
The increasing volume and complexity of genomic data pose significant challenges for effective data management and reuse. Public genomic data often undergo similar preprocessing across projects, leading to redundant or inconsistent datasets and inefficient use of computing resources. This is especially pertinent for bioinformaticians engaged in multiple projects. Tools have been created to address challenges in managing and accessing curated genomic datasets, however, the practical utility of such tools becomes especially beneficial for users who seek to work with specific types of data or are technically inclined toward a particular programming language. Currently, there exists a gap in the availability of an R-specific solution for efficient data management and versatile data reuse.
RESULTS
Here we present ReUseData, an R software tool that overcomes some of the limitations of existing solutions and provides a versatile and reproducible approach to effective data management within R. ReUseData facilitates the transformation of ad hoc scripts for data preprocessing into Common Workflow Language (CWL)-based data recipes, allowing for the reproducible generation of curated data files in their generic formats. The data recipes are standardized and self-contained, enabling them to be easily portable and reproducible across various computing platforms. ReUseData also streamlines the reuse of curated data files and their integration into downstream analysis tools and workflows with different frameworks.
CONCLUSIONS
ReUseData provides a reliable and reproducible approach for genomic data management within the R environment to enhance the accessibility and reusability of genomic data. The package is available at Bioconductor ( https://bioconductor.org/packages/ReUseData/ ) with additional information on the project website ( https://rcwl.org/dataRecipes/ ).
Topics: Data Management; Genomics; Software; Programming Languages; Workflow
PubMed: 38172657
DOI: 10.1186/s12859-023-05626-0 -
The Hastings Center Report Jan 2024Data infrastructure includes the bureaucratic, technical, and social mechanisms that assist in actions like data management, analysis, storage, and sharing. While issues...
Data infrastructure includes the bureaucratic, technical, and social mechanisms that assist in actions like data management, analysis, storage, and sharing. While issues like data sharing have been addressed in depth in bioethical literature, data infrastructure presents its own ethical considerations, apart from the actions (such as data sharing and data analysis) that it enables. This essay outlines some of these considerations-namely, the ethics of efficiency, the visibility of infrastructure, the power of standards, and the impact of new technologies-in order to invite the bioethics community to participate in conversations about infrastructure, as their expertise is both needed and welcomed.
Topics: Humans; Bioethical Issues; Bioethics; Information Dissemination
PubMed: 38390677
DOI: 10.1002/hast.1564 -
Histochemistry and Cell Biology Sep 2023Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have...
Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have increased both the spatial and temporal resolutions at which we examine those systems, as well as enabling visualisation of larger tissue volumes. These advances have huge potential but also generate ever increasing amounts of imaging data that must be stored and analysed. Public image repositories provide a critical scientific service through open data provision, supporting reproducibility of scientific results, access to reference imaging datasets and reuse of data for new scientific discovery and acceleration of image analysis methods development. The scale and scope of imaging data provides both challenges and opportunities for open sharing of image data. In this article, we provide a perspective influenced by decades of provision of open data resources for biological information, suggesting areas to focus on and a path towards global interoperability.
Topics: Reproducibility of Results; Image Processing, Computer-Assisted
PubMed: 37537341
DOI: 10.1007/s00418-023-02216-2 -
Methods in Molecular Biology (Clifton,... 2024In this chapter, we explore the application of high-throughput crop phenotyping facilities for phenotype data acquisition and the extraction of significant information... (Review)
Review
In this chapter, we explore the application of high-throughput crop phenotyping facilities for phenotype data acquisition and the extraction of significant information from the collected data through image processing and data mining methods. Additionally, the construction and outlook of crop phenotype databases are introduced and the need for global cooperation and data sharing is emphasized. High-throughput crop phenotyping significantly improves accuracy and efficiency compared to traditional measurements, making significant contributions to overcoming bottlenecks in the phenotyping field and advancing crop genetics.
Topics: Crops, Agricultural; Data Mining; Phenotype; Image Processing, Computer-Assisted; Data Management; High-Throughput Screening Assays
PubMed: 38656479
DOI: 10.1007/978-1-0716-3778-4_1 -
Nature Chemistry Apr 2024The varying quality of scientific reports is a well-recognized problem and often results from a lack of standardization and transparency in scientific publications. This... (Review)
Review
The varying quality of scientific reports is a well-recognized problem and often results from a lack of standardization and transparency in scientific publications. This situation ultimately leads to prominent complications such as reproducibility issues and the slow uptake of newly developed synthetic methods for pharmaceutical and agrochemical applications. In recent years, various impactful approaches have been advocated to bridge information gaps and to improve the quality of experimental protocols in synthetic organic publications. Here we provide a critical overview of these strategies and present the reader with a versatile set of tools to augment their standard procedures. We formulate eight principles to improve data management in scientific publications relating to data standardization, reproducibility and evaluation, and encourage scientists to go beyond current publication standards. We are aware that this is a substantial effort, but we are convinced that the resulting improved data situation will greatly benefit the progress of chemistry.
PubMed: 38548884
DOI: 10.1038/s41557-024-01470-8 -
Global Challenges (Hoboken, NJ) Jan 2024The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications... (Review)
Review
The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications within precision medicine. Efficient management, analysis, and interpretation of big data can pave the way for groundbreaking advancements in precision medicine. However, the unprecedented strides in the automated collection of large-scale molecular and clinical data have also introduced formidable challenges in terms of data analysis and interpretation, necessitating the development of novel computational approaches. Some potential challenges include the curse of dimensionality, data heterogeneity, missing data, class imbalance, and scalability issues. This overview article focuses on the recent progress and breakthroughs in the application of big data within precision medicine. Key aspects are summarized, including content, data sources, technologies, tools, challenges, and existing gaps. Nine fields-Datawarehouse and data management, electronic medical record, biomedical imaging informatics, Artificial intelligence-aided surgical design and surgery optimization, omics data, health monitoring data, knowledge graph, public health informatics, and security and privacy-are discussed.
PubMed: 38223896
DOI: 10.1002/gch2.202300163