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AusTraits: a curated plant trait database for the Australian flora
No full textAusTraits is a transformative database, containing measurements on the traits of Australia’s plant species, standardised from hundreds of disconnected primary sources. So far, data have been assembled from 139 distinct sources, describing more than 80 plant traits and over 19k species. A full list of sources is provided below.
To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource will also be made available,
Contributors
The project is jointly led by Dr Daniel Falster (University of New South Wales, Sydney) and Dr Rachael Gallagher (Macquarie University), with input from 127 contributors from over 59 institutions.
The following people and institutions have have contributed to building this resource.
Data contributors (individuals): Mark Adams, Tara Angevin, Anthony Bean, Biloni, Chris Blackman, Eleanor Bolza, David Bowman, Jason Bragg, Amber Briggs, John Brock, Jeff Burley, Geoff Burrows, Don Butler, Carter, Jane A. Catford, Gregory Chandler, Alex Chapman, Si-Chong Chen, Nguyen Ngoc Chinh, Robert Chinnock, David Christophel, Martin Chudnoff, Peter Clarke, Harold Trevor Clifford, Wendy Cooper, William Cooper, Ian Cowie, Lyn Craven, Michael Crisp, Erika Cross, Saul Cunningham, Ian Davidson, Matthew Denton, Desch, Dimitri, David Duncan, Marco Duretto, John M. Dwyer, Derek Eamus, Rebel Elick, John Evans, James Flynn, Carlos Fonseca, Paul Irwin Forster, Sean Gleason, Ethel Goble-Garratt, Goldsmith, Bruce Gray, Caroline Gross, Peter Grubb, Matthew Harrison, Foteini Hassiotou, Heady, Martin Henery, Lesley Hughes, Kate Hughes, John Huisman, Bernie Hyland, Muhammad Islam, Greg Jordan, Enrique Jurado, Greg Keighery, Juergen Kellerman, Kirsten Knox, Robert Kooyman, Etienne Laliberte, Hans Lambers, Byron Lamont, Daniel C. Laughlin, Michael Lawes, Emma Laxton, Caroline Lehmann, Michelle Leishman, Brendan Lepschi, Margaret Lewington, Janice Lord, Ian Lunt, Christopher Lusk, Anthony Manea, Neville Marchant, Abdurahim Martawijaya, Bruce Maslin, Robert Mason, James McCarthy, Daniel Metcalfe, Angela Moles, John Morgan, Huw Morgan, Andrew O’Reilly-Nugent, Grazyna Paczkowska, Paula Peeters, Burak Pekin, Lynda Prior, Jenny Read, Barbara Rice, Anna Richards, Bryan Roberts, Barbara Rye, Miguel de Salas, Susanne Schmidt, Ernst-Detlef Schulze, Andrew John Scott, Oey Djoen Seng, Santiago Soliveres, Jan Suda, Ian Thompson, David Tng, H. Toelken, Kyle Tomlinson, Malcolm Trudgeon, Erik Veneklaas, Peter Vesk, Mark Westoby, Judith Wheeler,Trevor Whiffin, Peter Wilson, Ian Wright & Amy Zanne
Data contributors (institutions): Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium
Data processing: Daniel Falster, Elizabeth Wenk, Caitlan Baxter, Sam Andrew, James Lawson, Stuart Allen
Project initiation and data compilation: Rachael Gallagher, Ian Wright
Funding: This work was supported by fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910), a grant from Macquarie University to Gallagher, and investment from the Australian Research Data Commons (ARDC), via their "Transformative data collections" (https://doi.org/10.47486/TD044) program. The ARDC is enabled by National Collaborative Research Investment Strategy (NCRIS).
Accessing and use of data
AusTraits will be released under an open source licence (CC-BY), enabling re-use by the community, once our paper describing the data resource becomes public (in 2020). In the meantime, access to the the data resource is restricted.
A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors:
Citation pending
In addition, we encourage users you to cite the original data sources, wherever possible.
Contributing
We envision AusTraits as an on-going collaborative community resource that:
Increases our collective understanding the Australian flora; and
Facilitates accumulating and sharing of trait data;
Builds a sense of community among contributors and users; and
Aspires to fully transparent and reproducible research of highest standard.
As a community resource, we are very keen for people to contribute. Here are some of the ways you can contribute:
Reporting Errors: If you notice a possible error in AusTraits, please post an issue on GitHub .
Refining documentation: We welcome additions and edits that make using the existing data or adding new data easier for the community.
Contributing new data: We gladly accept new data contributions to AusTraits. For full instructions on preparing data for inclusion in AusTraits, please got to https://github.com/traitecoevo/austraits.build.
Structure of AusTraits data
The compiled AusTraits database has the following main components:
austraits
├── traits
├── sites
├── methods
├── excluded_data
├── taxonomy
├── definitions
├── contributors
└── build_info
These elements include all the data and contextual information submitted with each contributed datasets.
Full details on each of these components and columns therein are contained within the document Austraits_dictionary.html and within the file definitions.yml.
Full details on all original sources used to generate this compilation and variables collected are available within the download
AusTraits: a curated plant trait database for the Australian flora
No full textAusTraits is a transformative database, containing measurements on the traits of Australia’s plant species, standardised from hundreds of disconnected primary sources. So far, data have been assembled from 139 distinct sources, describing more than 80 plant traits and over 19k species. A full list of sources is provided below.
To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource will also be made available,
Contributors
The project is jointly led by Dr Daniel Falster (University of New South Wales, Sydney) and Dr Rachael Gallagher (Macquarie University), with input from 127 contributors from over 59 institutions.
The following people and institutions have have contributed to building this resource.
Data contributors (individuals): Mark Adams, Tara Angevin, Anthony Bean, Biloni, Chris Blackman, Eleanor Bolza, David Bowman, Jason Bragg, Amber Briggs, John Brock, Jeff Burley, Geoff Burrows, Don Butler, Carter, Jane A. Catford, Gregory Chandler, Alex Chapman, Si-Chong Chen, Nguyen Ngoc Chinh, Robert Chinnock, David Christophel, Martin Chudnoff, Peter Clarke, Harold Trevor Clifford, Wendy Cooper, William Cooper, Ian Cowie, Lyn Craven, Michael Crisp, Erika Cross, Saul Cunningham, Ian Davidson, Matthew Denton, Desch, Dimitri, David Duncan, Marco Duretto, John M. Dwyer, Derek Eamus, Rebel Elick, John Evans, James Flynn, Carlos Fonseca, Paul Irwin Forster, Sean Gleason, Ethel Goble-Garratt, Goldsmith, Bruce Gray, Caroline Gross, Peter Grubb, Matthew Harrison, Foteini Hassiotou, Heady, Martin Henery, Lesley Hughes, Kate Hughes, John Huisman, Bernie Hyland, Muhammad Islam, Greg Jordan, Enrique Jurado, Greg Keighery, Juergen Kellerman, Kirsten Knox, Robert Kooyman, Etienne Laliberte, Hans Lambers, Byron Lamont, Daniel C. Laughlin, Michael Lawes, Emma Laxton, Caroline Lehmann, Michelle Leishman, Brendan Lepschi, Margaret Lewington, Janice Lord, Ian Lunt, Christopher Lusk, Anthony Manea, Neville Marchant, Abdurahim Martawijaya, Bruce Maslin, Robert Mason, James McCarthy, Daniel Metcalfe, Angela Moles, John Morgan, Huw Morgan, Andrew O’Reilly-Nugent, Grazyna Paczkowska, Paula Peeters, Burak Pekin, Lynda Prior, Jenny Read, Barbara Rice, Anna Richards, Bryan Roberts, Barbara Rye, Miguel de Salas, Susanne Schmidt, Ernst-Detlef Schulze, Andrew John Scott, Oey Djoen Seng, Santiago Soliveres, Jan Suda, Ian Thompson, David Tng, H. Toelken, Kyle Tomlinson, Malcolm Trudgeon, Erik Veneklaas, Peter Vesk, Mark Westoby, Judith Wheeler,Trevor Whiffin, Peter Wilson, Ian Wright & Amy Zanne
Data contributors (institutions): Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium
Data processing: Daniel Falster, Elizabeth Wenk, Caitlan Baxter, Sam Andrew, James Lawson, Stuart Allen
Project initiation and data compilation: Rachael Gallagher, Ian Wright
Funding: This work was supported by fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910), a grant from Macquarie University to Gallagher.
Accessing and use of data
AusTraits will be released under an open source licence (CC-BY), enabling re-use by the community, once our paper describing the data resource becomes public (in 2020). In the meantime, access to the the data resource is restricted.
A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors:
Citation pending
In addition, we encourage users you to cite the original data sources, wherever possible.
Contributing
We envision AusTraits as an on-going collaborative community resource that:
Increases our collective understanding the Australian flora; and
Facilitates accumulating and sharing of trait data;
Builds a sense of community among contributors and users; and
Aspires to fully transparent and reproducible research of highest standard.
As a community resource, we are very keen for people to contribute. Here are some of the ways you can contribute:
Reporting Errors: If you notice a possible error in AusTraits, please post an issue on GitHub .
Refining documentation: We welcome additions and edits that make using the existing data or adding new data easier for the community.
Contributing new data: We gladly accept new data contributions to AusTraits. For full instructions on preparing data for inclusion in AusTraits, please got to https://github.com/traitecoevo/austraits.build.
Structure of AusTraits data
The compiled AusTraits database has the following main components:
austraits
├── traits
├── sites
├── methods
├── excluded_data
├── taxonomy
├── definitions
├── contributors
└── build_info
These elements include all the data and contextual information submitted with each contributed datasets.
Full details on each of these components and columns therein are contained within the document Austraits_dictionary.html and within the file definitions.yml.
Full details on all original sources used to generate this compilation and variables collected are available within the download
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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