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Patterns (New York, N.Y.) Sep 2021Reproducible computational research (RCR) is the keystone of the scientific method for analyses, packaging the transformation of raw data to published results. In... (Review)
Review
Reproducible computational research (RCR) is the keystone of the scientific method for analyses, packaging the transformation of raw data to published results. In addition to its role in research integrity, improving the reproducibility of scientific studies can accelerate evaluation and reuse. This potential and wide support for the FAIR principles have motivated interest in metadata standards supporting reproducibility. Metadata provide context and provenance to raw data and methods and are essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described how metadata enable reproducible computational research. This review employs a functional content analysis to identify metadata standards that support reproducibility across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications. Our review provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.
PubMed: 34553169
DOI: 10.1016/j.patter.2021.100322 -
RoFo : Fortschritte Auf Dem Gebiete Der... May 2024Worldwide, the study and examination of human remains and the circumstances of their acquisition for anatomical collection have received great interest. As part of...
Worldwide, the study and examination of human remains and the circumstances of their acquisition for anatomical collection have received great interest. As part of provenance research projects, a large number of collections are being investigated to determine whether the human remains have been acquired in a correct or unlawful way because the people could have been killed in order to be used as "anthropological objects" for research purposes and to become so-called "specimens". These topics have also been addressed by the Institute of Anatomy at the University Medical Center Rostock. The role of radiology in this interdisciplinary project will be presented using selected examples.The anatomical collection at the University of Rostock includes 40 human skulls, 14 plaster casts, 6 Egyptian mummy heads, and 1 full-body mummy. In addition to the examination by a historian, an anthropologist, and forensic pathologists, additional computed tomography was carried out on nine skulls and the full-body mummy. Micro-computed tomography was also carried out on seven skulls in order to enable a look behind the mummification material and tissue remains.(Micro-)computed tomography was able to close diagnostic gaps and the results presented some rather unexpected findings.Due to interdisciplinary collaboration, individual fates could be determined, which provided information about the individual's life and death circumstances. None of the examined individuals showed evidence of colonial-era injustice or the use of violence that would have led to their inclusion in the collection. (Micro-)computed tomography was a valuable addition to this provenance research project. · Computed tomography enhances interdisciplinary provenance research projects.. · Computed tomography enables a non-destructive examination of human remains.. · The future of research and presentation of human remains will increasingly be virtual.. · Steinhagen I, Brinker U, Kolbe V et al. The role of radiology in provenance research - experiences from the collaboration between radiology and anatomy at the University of Rostock and future perspectives. Fortschr Röntgenstr 2024; DOI 10.1055/a-2303-0312.
PubMed: 38744319
DOI: 10.1055/a-2303-0312 -
New Biotechnology Dec 2023AI development in biotechnology relies on high-quality data to train and validate algorithms. The FAIR principles (Findable, Accessible, Interoperable, and Reusable) and...
AI development in biotechnology relies on high-quality data to train and validate algorithms. The FAIR principles (Findable, Accessible, Interoperable, and Reusable) and regulatory frameworks such as the In Vitro Diagnostic Regulation (IVDR) and the Medical Device Regulation (MDR) specify requirements on specimen and data provenance to ensure the quality and traceability of data used in AI development. In this paper, a framework is presented for recording and publishing provenance information to meet these requirements. The framework is based on the use of standardized models and protocols, such as the W3C PROV model and the ISO 23494 series, to capture and record provenance information at various stages of the data generation and analysis process. The framework and use case illustrate the role of provenance information in supporting the development of high-quality AI algorithms in biotechnology. Finally, the principles of the framework are illustrated in a simple computational pathology use case, showing how specimen and data provenance can be used in the development and documentation of an AI algorithm. The use case demonstrates the importance of managing and integrating distributed provenance information and highlights the complex task of considering factors such as semantic interoperability, confidentiality, and the verification of authenticity and integrity.
Topics: Algorithms; Biotechnology; Artificial Intelligence
PubMed: 37758054
DOI: 10.1016/j.nbt.2023.09.006 -
The Journal of Consumer Affairs 2022This article advances the riveting discussion on how this special issue contributes to the consumer well-being literature. Specifically, this article endeavors to...
This article advances the riveting discussion on how this special issue contributes to the consumer well-being literature. Specifically, this article endeavors to present an eclectic account of how the pandemics has had a lasting impact on the consumer well-being, its provenance and future research priorities for academics and practice. First, it briefly discusses the origin and relevance of the evolving issue of consumer well-being during pandemics. Second, it presents several directions for future research and third, it offers key insights for policymakers. It includes multiple research priorities that present vastly contrasting manifestations of consumer well-being. This article argues that future research will need to examine the drivers of consumer well-being during pandemics, the mechanisms that underlie the influence of pandemics on consumer well-being and the boundary conditions that accentuate/mitigate the influence of pandemic-induced factors.
PubMed: 35603324
DOI: 10.1111/joca.12445 -
Patterns (New York, N.Y.) May 2020Data provenance is a machine-readable summary of the collection and computational history of a dataset. Data provenance confers or adds value to a dataset, helps...
Data provenance is a machine-readable summary of the collection and computational history of a dataset. Data provenance confers or adds value to a dataset, helps reproduce computational analyses, or validates scientific conclusions. The people of the End-to-End Provenance Project are a community of professionals who have developed software tools to collect and use data provenance.
PubMed: 33205093
DOI: 10.1016/j.patter.2020.100016 -
The FEBS Journal Jan 2022The FEBS Journal, a leading multidisciplinary journal in the life sciences, publishes high-impact papers on diverse topics relating to molecular mechanisms underpinning...
The FEBS Journal, a leading multidisciplinary journal in the life sciences, publishes high-impact papers on diverse topics relating to molecular mechanisms underpinning biological processes. Here, Editor-in-Chief Seamus Martin discusses the critical importance of data provenance and data integrity to the scientific method and discusses some of the highlights from 2021 at The FEBS Journal.
PubMed: 34982855
DOI: 10.1111/febs.16332 -
Cytotechnology Jul 2002Cultured cell lines have become an extremely valuable resource, both in academic research and in industrial biotechnology. However, their value is frequently compromised...
Cultured cell lines have become an extremely valuable resource, both in academic research and in industrial biotechnology. However, their value is frequently compromised by misidentification and undetected microbial contamination. As detailed elsewhere in this volume, the technology, both simple and sophisticated, is available to remedy the problems of misidentification and contamination, given the will to apply it. Combined with proper records of the origin and history of the cell line, assays for authentication and contamination contribute to the provenance of the cell line. Detailed records should start from the initiation or receipt of the cell line, and should incorporate data on the donor as well as the tissue from which the cell line was derived, should continue with details of maintenance, and include any accidental as well as deliberate deviations from normal maintenance. Records should also contain details of authentication and regular checks for contamination. With this information, preferably stored in a database, and suitable backed up, the provenance of the cell line so created makes the cell line a much more valuable resource, fit for validation in industrial applications and more likely to provide reproducible experimental results when disseminated for research in other laboratories.
PubMed: 19003293
DOI: 10.1023/A:1022949730029 -
Patterns (New York, N.Y.) Aug 2020Deep learning, a set of approaches using artificial neural networks, has generated rapid recent advancements in machine learning. Deep learning does, however, have the...
Deep learning, a set of approaches using artificial neural networks, has generated rapid recent advancements in machine learning. Deep learning does, however, have the potential to reduce the reproducibility of scientific results. Model outputs are critically dependent on the data and processing approach used to initially generate the model, but this provenance information is usually lost during model training. To avoid a future reproducibility crisis, we need to improve our deep-learning model management. The FAIR principles for data stewardship and software/workflow implementation give excellent high-level guidance on ensuring effective reuse of data and software. We suggest some specific guidelines for the generation and use of deep-learning models in science and explain how these relate to the FAIR principles. We then present dtoolAI, a Python package that we have developed to implement these guidelines. The package implements automatic capture of provenance information during model training and simplifies model distribution.
PubMed: 33205122
DOI: 10.1016/j.patter.2020.100073 -
Frontiers in Genetics 2022Fair and equitable benefit sharing of genetic resources is an expectation of the Nagoya Protocol. Although the Nagoya Protocol does not yet formally apply to Digital...
Fair and equitable benefit sharing of genetic resources is an expectation of the Nagoya Protocol. Although the Nagoya Protocol does not yet formally apply to Digital Sequence Information ("DSI"), discussions are currently underway regarding to include such data through ongoing Convention on Biological Diversity ("CBD") negotiations. While Indigenous Peoples and Local Communities ("IPLC") expect the value generated from genomic data to be subject to benefit sharing arrangements, a range of views are currently being expressed by Nation States, IPLC and other stakeholders. The use of DSI gives rise to unique considerations, creating a gray area as to how it should be considered under the Nagoya Protocol's Access and Benefit Sharing ("ABS") principles. One way for benefit sharing to be enhanced is through the connection of data to proper provenance information. A significant development is the use of digital labeling systems to ensure that the origin of samples is appropriately disclosed. The Traditional Knowledge and Biocultural Labels initiative offers a practical option for data provided to genomic databases. In particular, the BioCultural Labels ("BC Labels") are a mechanism for Indigenous communities to identify and maintain provenance, origin and authority over biocultural material and data generated from Indigenous land and waters held in research, cultural institutions and data repositories. This form of cultural metadata adds value to the research endeavor and the creation of Indigenous fields within databases adds transparency and accountability to the research environment.
PubMed: 36212139
DOI: 10.3389/fgene.2022.1014044 -
Frontiers in Pharmacology 2020The Celtic linguistic community dominated large spans of Central and Western Europe between 800 BC and 500 AD, but knowledge of their traditional medicine is very... (Review)
Review
The Celtic linguistic community dominated large spans of Central and Western Europe between 800 BC and 500 AD, but knowledge of their traditional medicine is very limited. Multiple progressive plant gains in Neolithic settlements along the Danube and up the Rhine valleys suggested that taxon diversity of gathered plants peaked at the Balkans and was subsequently reduced as crop and gathered plants packages were adopted and dispersed throughout Neolithic Europe. This process coincided with the Bronze Age migration of the R1b proto-Celtic tribes, and their herbal traditions were occasionally recorded in the classic Greco-Roman texts on herbal medicines. The provenance of Celtic (Gallic) healing methods and magical formulas as recorded by Pliny, Scribonius Largus, and Marcellus Empiricus can still be found in the first part of the medieval Welsh (Cymry) herbal manuscript (recipes 1-188). Although the majority of I recipes were based on the Mediterranean herbal tradition of Dioscorides and Macer Floridus, they preserved the unique herbal preparation signatures distinct from continental and Anglo-Saxon counterparts in increased use of whey and ashes as vehicles for formulation of herbal remedies. Six plants could be hypothetically attributed to the Celtic (Welsh) herbal tradition including foxglove ( L.), corn bellflower ( L.), self-heal ( L.), sharp dock ( Murray), water pimpernel ( L.), and river startip ( L.) This review provides initial evidence for traces of Celtic framework in the Welsh herbal tradition and warrants further investigations of bioactivity and clinical applications of the described plant leads.
PubMed: 32184721
DOI: 10.3389/fphar.2020.00105