1,721,029 research outputs found
mBRAVE: The Multiplex Barcode Research And Visualization Environment
No full textWidespread interest in the study of metabarcoding has resulted in data proliferation and the development of a multitude of powerful computational tools. Yet consistent and reproducible interpretation of the data remains challenging. The integration of different data types, software tools, and analytical parameters pose a barrier to scaling research. Further, though the majority of the necessary tools for performing these analyses are already implemented, there is limited support for high throughput analysis due to the requirement for heavy computational capacity. As a result of these complexities, many researchers lack the time, training, or infrastructure to work with larger datasets.
mBRAVE, the Multiplex Barcode Research And Visualization Environment, is a cloud-based data storage and analytics platform with standardized pipelines and a sophisticated web interface for transforming raw high-throughput sequencing (HTS) data into biological insights. mBRAVE integrates common analytical methods and links to the Barcode of Life Data (BOLD) System for reference datasets, presenting users with the ability to analyze large volumes of data, without requiring special technical training. mBRAVE's cloud architecture provides centralized and automated storage and compute capacity, thereby reducing the burden on individual researchers.
The mBRAVE platform seeks to alleviate the main informatic challenges faced by the metabarcoding research community: the storage and consistent interpretation of HTS data. It is now available for researcher use at www.mbrave.net
BOLD & mBRAVE: Purpose-Built Research Data Platforms in the Biodiversity Domain
No full textUpdate on the BOLD and mBRAVE projects, part of the International Barcode of Life Project.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Bringing Genomics to Diversity: Barcode of Life Database System & Multiplex Barcode Research and Visualization Environment
No full textDescription of the software development project funded by CANARIE.</p
WF.ACTIAS: A workflow for a better integration of biodiversity data from diverse sources
No full textInternational audienceOur knowledge of global biodiversity remains incomplete and beset by knowledge shortfalls affecting both the census of species (i.e. the Linnean shortfall) and our understanding of their distributions (i.e. the Wallacean shortfall; Hortal et al. 2015). While alarming rates of species extinction have been reported in most groups of organisms, our capacity to assess extinction threats is limited by these shortfalls and it has become imperative to optimize our use of existing information for the analyses of biodiversity data. There are two major challenges when integrating biodiversity data from heterogeneous sources to ultimately analyzing them:The frequent disparity in taxon names used to refer to the same organisms;Geographical inconsistencies on specimen information. The first refers to disagreements about the taxon concepts attached to names alongside the different interpretations and applications (e.g. gender agreement in taxonomic names) of the existing nomenclatural rules that ensure universality and stability of scientific names. The development of new methods for species delineation, and in particular with the growing integration of genetic data in the practice of taxonomy (e.g. DNA barcoding; Ratnasingham and Hebert 2013), has increased our ability to discriminate closely related species. This enhances the resolution level at which biodiversity is documented, described and analyzed(Goldstein and DeSalle 2011). One frequent outcome is the redefinition of species boundaries; either through merging (synonymy) or splitting of previously recognized species. In understudied groups such as insects, the resulting inflation of names, sometimes provisional, further defies the reconciliation of names used by different sources.The second challenge refers to the completeness and accuracy of geographical information. Specimen records in biodiversity databases often lack GPS coordinates. Consequently we need to accurately infer the latitude and longitude from place names. Other frequent inaccuracies include erroneous georeferencing, imprecision and/or error in the location of a record (Soberón and Peterson 2004).Integration of data on the basis of taxon names and their geographic information is a major challenge that either results in excluding a significant number of records, or in merging incompatible records, leading to erroneous outcomes. Therefore, we have developed WF.ACTIAS, a computational workflow that gathers data from several sources and provides the user with tools to make objective and reproducible decisions to assign records to a consensus species name, while detecting and correcting geographical inconsistencies. Its main objective is to automate a process that can integrate information about nomenclature, taxon concepts and geographical information to reconcile taxon names from different sources. Here, we present the WF.ACTIAS workflow in the context of the analysis of diversity in two sister families of moths – the Saturniidae and Sphingidae. Species boundaries in these insects have been thoroughly and comprehensively revisited through the integration of DNA barcodes and we are tackling the reconciliation of taxon names in ca. 282 000 records of which more than 77 000 have DNA barcodes. The outcome of this data integration is essential to study patterns of biodiversity and distributions and sets the ground to extend this process to other groups of organisms
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