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Supplementary file 2 for "Pushes and pulls from below: anatomical variation, articulation and sound change": the data
<p>The data (as TAB-separated .TSV files and .RData standard R data files) and Rmarkdown script needed to reproduce the results reported in the main paper as a single .TAR.XZ archive.</p> <p>Please note that the actual results obtained when compiling this script may differ slightly from those reported in the paper, especially for Markov-Chain Monte Carlo (due to the heavy use of random numbers), but also for the Maximum Likelihood (due to differences between particular BLAS/LAPACK implementations).</p> <p>The first compilation of this script is quite expensive computationally (on an Intel Core i7-3770 \@ 3.40 GHz with 32 Gb RAM this took about 25 hours), but the next ones are much faster as the most expensive results are cached locally.</p>
Supplementary material 7 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document contains an annotated set of data quality checks that participants report they use when evaluating and cleaning datasets. These items outline how participants are judging if the data suits their purpose.
Supplementary material 3 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
The informed consent request and workshop survey questions given to participants after the workshop each day for 4 consecutive days.
Supplementary material 2 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document shows just the questions we asked the applicants who applied to participate in this Georeferencing for Research Use workshop. We used a Google Form to deliver these questions and collect responses. It is both an application and serves as our pre-workshop survey.
Supplementary material 8 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of desired future workshop topics that were listed by participants on the last day of the workshop.
Supplementary material 6 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of topics to be covered in an ideal workshop as identified by workshop applicants in the workshop call for participation. We incorporated as many as possible that also fit our scope.
Supplementary material 5 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Questions we asked in the Georeferencing for Research Follow Up Survey done 3 months after the workshop.
Supplementary material 4 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Three months after the workshop, participants were surveyed to assess what workshop-related knowledge and materials were being used and disseminated to others. This document summarized data collected in this particular survey.
Supplementary material 1 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Darwin Core Archive file downloaded from the iDigBio portal for use in the Georeferencing for Research Use workshop. Total 25,429 records, accessed on 2016-08-29. Collections contributing to the record set are listed in the archive records.citation.txt file. Dataset GUID: a69d1541-4726-465d-84ad-50c7ed556eee
Supplementary material 3 from: Petersen M, Hoffmann J, Glöckler F (2019) Access to Geosciences – Ways and Means to share and publish collection data. Research Ideas and Outcomes 5: e32987. https://doi.org/10.3897/rio.5.e32987
Programm of the two-day workshop Access to Geosciences: sharing and publishing data related to paleontological, mineralogical, and petrological objects using a common data standard. Museum für Naturkunde, 29-30 May 2017
Supplementary material 2 from: Petersen M, Hoffmann J, Glöckler F (2019) Access to Geosciences – Ways and Means to share and publish collection data. Research Ideas and Outcomes 5: e32987. https://doi.org/10.3897/rio.5.e32987
Results of the survey on geoscientific collection data. Names, institutions and contact details are anonymized
Supplementary Table S2 - Mass Spec Data
<p>Mass spec data from two different co-immunoprecipitations using Plasmodium falciparum PF3D7_1102500 as bait under crosslinked and non-crosslinked conditions.</p>
Supplementary material 2 from: Zhao Y, Liu X-z, Bai F-y (2019) Four new species of Tremella (Tremellales, Basidiomycota) based on morphology and DNA sequence data. MycoKeys 47: 75-95. https://doi.org/10.3897/mycokeys.47.29180
Supplementary material 2 from: Zhao Y, Liu X-z, Bai F-y (2019) Four new species of Tremella (Tremellales, Basidiomycota) based on morphology and DNA sequence data. MycoKeys 47: 75-95. https://doi.org/10.3897/mycokeys.47.29180
Supplementary material 1 from: Zhao Y, Liu X-z, Bai F-y (2019) Four new species of Tremella (Tremellales, Basidiomycota) based on morphology and DNA sequence data. MycoKeys 47: 75-95. https://doi.org/10.3897/mycokeys.47.29180
Supplementary material 1 from: Zhao Y, Liu X-z, Bai F-y (2019) Four new species of Tremella (Tremellales, Basidiomycota) based on morphology and DNA sequence data. MycoKeys 47: 75-95. https://doi.org/10.3897/mycokeys.47.29180
Supplementary Data: Testing the uniqueness of deep terrestrial life
<p>.R script and data for analyses.</p>
Interpretable semi-supervised population prediction and disaggregation using ancillary data - Supplementary Material
<p>Interpretable semi-supervised population prediction and disaggregation using ancillary data - Supplementary Material</p> <p>(details about the datasets + access to datasets + access to source code)</p>
Supplementary Data for risk management
<p>Data for reservoir inflows and lateral inflows are listed in the file "Inflows". Data for reservoir characteristcs and river flood routing parameters are listed in the file "characteristics of reservoirs and river flood routing parameters". Matlab codes for NSGA-III are listed in the file "nsga-iii".</p>
Supplementary fish data for https://doi.org/10.1101/480335
<p>Distance matrices for the fish dataset.</p> <p>More details on the data collection methods can be found in Fourtune, L., Paz‐Vinas, I., Loot, G., Prunier, J. G., & Blanchet, S. (2016). Lessons from the fish: a multi‐species analysis reveals common processes underlying similar species‐genetic diversity correlations. <em>Freshwater Biology</em>, <em>61</em>(11), 1830-1845.</p> <p>A commented R script to use these data is provided at https://github.com/franckjabot/metacommunity-analysis-script</p> <p> </p>
Supplementary simulation data for https://doi.org/10.1101/480335
<p>Distance matrices for the simulated datasets.</p> <p>A commented R script to use these data is provided at https://github.com/franckjabot/metacommunity-analysis-script</p>
Supplementary plant data for https://doi.org/10.1101/480335
<p>Distance matrices for the aquatic plants, associated to Jabot et al. 2019. Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition. DOI: https://doi.org/10.1101/480335</p> <p> </p> <p> </p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.