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FIGURE 7 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 7. Bar graph of similarity for different guide formats with the highest and lowest performer truncated from each group. 7A: presence/absence data using Sdice; 7B: relative abundance data using Sbc. 'Experts' combines data from the authors, who each have substantial paleontology experience.
Replication Package: Unboxing Default Argument Breaking Changes in 1 + 2 Data Science Libraries in Python
<p><strong>Replication Package</strong></p> <p>This repository contains data and source files needed to replicate our work described in the paper "Unboxing Default Argument Breaking Changes in Scikit Learn".</p> <p><strong>Requirements</strong></p> <p>We recommend the following requirements to replicate our study:</p> <ol> <li>Internet access</li> <li>At least 100GB of space</li> <li>Docker installed</li> <li>Git installed</li> </ol> <p><strong>Package Structure</strong></p> <p>We relied on Docker containers to provide a working environment that is easier to replicate. Specifically, we configure the following containers:</p> <ul> <li><code>data-analysis</code>, an R-based Container we used to run our data analysis.</li> <li><code>data-collection</code>, a Python Container we used to collect Scikit's default arguments and detect them in client applications.</li> <li><code>database</code>, a Postgres Container we used to store clients' data, obtainer from Grotov et al.</li> <li><code>storage</code>, a directory used to store the data processed in <code>data-analysis</code> and <code>data-collection</code>. This directory is shared in both containers.</li> <li><code>docker-compose.yml</code>, the Docker file that configures all containers used in the package.</li> </ul> <p>In the remainder of this document, we describe how to set up each container properly.</p> <p><strong>Using VSCode to Setup the Package</strong></p> <p>We selected VSCode as the IDE of choice because its extensions allow us to implement our scripts directly inside the containers. In this package, we provide configuration parameters for both <code>data-analysis</code> and <code>data-collection</code> containers. This way you can directly access and run each container inside it without any specific configuration.</p> <p>You first need to set up the containers</p> <pre><code>$ cd /replication/package/folder $ docker-compose build $ docker-compose up # Wait docker creating and running all containers </code></pre> <p>Then, you can open them in Visual Studio Code:</p> <ol> <li>Open VSCode in project root folder</li> <li>Access the command palette and select "Dev Container: Reopen in Container" <ol> <li>Select either <em>Data Collection</em> or <em>Data Analysis</em>.</li> </ol> </li> <li>Start working</li> </ol> <p>If you want/need a more customized organization, the remainder of this file describes it in detail.</p> <p><strong>Longest Road: Manual Package Setup</strong></p> <p><strong>Database Setup</strong></p> <p>The database container will automatically restore the dump in <code>dump_matroskin.tar</code> in its first launch. To set up and run the container, you should:</p> <p>Build an image:</p> <pre><code>$ cd ./database $ docker build --tag 'dabc-database' . $ docker image ls REPOSITORY TAG IMAGE ID CREATED SIZE dabc-database latest b6f8af99c90d 50 minutes ago 18.5GB </code></pre> <p>Create and enter inside the container:</p> <pre><code>$ docker run -it --name dabc-database-1 dabc-database $ docker exec -it dabc-database-1 /bin/bash root# psql -U postgres -h localhost -d jupyter-notebooks jupyter-notebooks=# \dt List of relations Schema | Name | Type | Owner --------+-------------------+-------+------- public | Cell | table | root public | Code_cell | table | root public | Md_cell | table | root public | Notebook | table | root public | Notebook_features | table | root public | Notebook_metadata | table | root public | repository | table | root </code></pre> <p>If you got the tables list as above, your database is properly setup.</p> <p>It is important to mention that this database is extended from the one provided by <a href="https://markdowntohtml.com/">Grotov et al.</a>. Basically, we added three columns in the table <code>Notebook_features</code> (<code>API_functions_calls</code>, <code>defined_functions_calls</code>, and<code>other_functions_calls</code>) containing the function calls performed by each client in the database.</p> <p><strong>Data Collection Setup</strong></p> <p>This container is responsible for collecting the data to answer our research questions. It has the following structure:</p> <ul> <li><code>dabcs.py</code>, extract DABCs from Scikit Learn source code, and export them to a CSV file.</li> <li><code>dabcs-clients.py</code>, extract function calls from clients and export them to a CSV file. We rely on a modified version of <a href="https://markdowntohtml.com/">Matroskin</a> to leverage the function calls. You can find the tool's source code in the `matroskin`` directory.</li> <li><code>Makefile</code>, commands to set up and run both <code>dabcs.py</code> and <code>dabcs-clients.py</code></li> <li><code>matroskin</code>, the directory containing the modified version of matroskin tool. We extended the library to collect the function calls performed on the client notebooks of Grotov's dataset.</li> <li><code>storage</code>, a docker volume where the data-collection should save the exported data. This data will be used later in <a href="https://markdowntohtml.com/#data-analysis-setup">Data Analysis</a>.</li> <li><code>requirements.txt</code>, Python dependencies adopted in this module.</li> </ul> <p>Note that the container will automatically configure this module for you, e.g., install dependencies, configure matroskin, download scikit learn source code, etc. For this, you must run the following commands:</p> <pre><code>$ cd ./data-collection $ docker build --tag "data-collection" . $ docker run -it -d --name data-collection-1 -v $(pwd)/:/data-collection -v $(pwd)/../storage/:/data-collection/storage/ data-collection $ docker exec -it data-collection-1 /bin/bash $ ls Dockerfile Makefile config.yml dabcs-clients.py dabcs.py matroskin storage requirements.txt utils.py </code></pre> <p>If you see project files, it means the container is configured accordingly.</p> <p><strong>Data Analysis Setup</strong></p> <p>We use this container to conduct the analysis over the data produced by the <a href="https://markdowntohtml.com/#data-collection-setup">Data Collection</a> container. It has the following structure:</p> <ul> <li><code>dependencies.R</code>, an R script containing the dependencies used in our data analysis.</li> <li><code>data-analysis.Rmd</code>, the R notebook we used to perform our data analysis</li> <li><code>datasets</code>, a docker volume pointing to the <code>storage</code> directory.</li> </ul> <p>Execute the following commands to run this container:</p> <pre><code>$ cd ./data-analysis $ docker build --tag "data-analysis" . $ docker run -it -d --name data-analysis-1 -v $(pwd)/:/data-analysis -v $(pwd)/../storage/:/data-collection/datasets/ data-analysis $ docker exec -it data-analysis-1 /bin/bash $ ls data-analysis.Rmd datasets dependencies.R Dockerfile figures Makefile </code></pre> <p>If you see project files, it means the container is configured accordingly.</p> <p>A note on <code>storage</code> shared folder</p> <p>As mentioned, the <code>storage</code> folder is mounted as a volume and shared between <code>data-collection</code> and <code>data-analysis</code> containers. We compressed the content of this folder due to space constraints. Therefore, before starting working on <a href="https://markdowntohtml.com/#data-collection-setup">Data Collection</a> or <a href="https://markdowntohtml.com/#data-analysis-setup">Data Analysis</a>, make sure you extracted the compressed files. You can do this by running the <code>Makefile</code> inside <code>storage</code> folder.</p> <pre><code>$ make unzip # extract files $ ls clients-dabcs.csv clients-validation.csv dabcs.csv Makefile scikit-learn-versions.csv versions.csv $ make zip # compress files $ ls csv-files.tar.gz Makefile</code></pre>
Fig. 22 in Type Specimens of Halacarid Mites by Dr. N. G. Makarova Relocated in the Collection of the National Museum of Nature and Science, Tsukuba, Japan
Fig. 22.ɹCopidognathus rombus, paratype ˁ NSMT-Ac 14705. Body (A), gnathosoma (B) (Phase-contrast micrographs). Scale bars for A=100 µm, B=50 µm.
Fig. 14 in Type Specimens of Halacarid Mites by Dr. N. G. Makarova Relocated in the Collection of the National Museum of Nature and Science, Tsukuba, Japan
Fig. 14.ɹHalacarellus longus [nomen nudum], ˂ NSMT-Ac 14709 (No. 7) mounted on the glass slide of Copidognathus rombus. Body (A), gnathosoma (B) (Phase-contrast micrographs). Scale bars for A=100 µm, B=50 µm.
Fig. 5 in Type Specimens of Halacarid Mites by Dr. N. G. Makarova Relocated in the Collection of the National Museum of Nature and Science, Tsukuba, Japan
Fig. 5.ɹThalassarachna aculeata, paratype ˂ NSMT-Ac 14696. Body (A), genitoanal region (B), gnathosoma (C). Scale bars for A=100 µm, BC=50 µm.
Figure 3 in Equity and career-life balance in marine mammal science?
Figure 3. Survey responses from women (yellow) and men (green) in the Society of Marine Mammalogy (including students) showing reactions to the listed statements (from 1 = strongly disagree to 5 = strongly agree). Box plots are shown for median (heaviest color shading and stronger line) and interquartile range with whiskers for minimum and maximum values.
Figure 3 from: Schuette S, Folk RA, Cantley JT, Martine CT (2018) The hidden Heuchera: How science Twitter uncovered a globally imperiled species in Pennsylvania, USA. PhytoKeys 96: 87-97. https://doi.org/10.3897/phytokeys.96.23667
Figure 3 Comparisons of flowers and single petals (adaxial surface) of three Heuchera species co-occurring in PA, WV, and VA, based on spirit-preserved materials: Heuchera alba (a, d North Fork Mountain, WV; Folk 63 [deposited at OS]), Heuchera pubescens (b, e Rocky Knob Overlook, Blue Ridge Parkway, VA; Folk 100 [deposited at OS]), and unhybridized H. americana (i.e. H. americana var. americana c, f Chestoa Overlook, Blue Ridge Parkway; Folk 92 [deposited at OS]). Dotted gray lines show degree of hypanthium zygomorphy. Both scale bars represent 5 mm; the left-hand scale bar applies to a–c the right-hand bar is for d–f. Illustrations by R. Folk
Figure 2 from: Schuette S, Folk RA, Cantley JT, Martine CT (2018) The hidden Heuchera: How science Twitter uncovered a globally imperiled species in Pennsylvania, USA. PhytoKeys 96: 87-97. https://doi.org/10.3897/phytokeys.96.23667
Figure 2 Images a–d Flowers of four Heuchera taxa overlapping in range in PA, WV, and VA. Flowers are shown at the original angle on the inflorescence; with the exception of the wild accession in (d), all flowers were obtained under common greenhouse conditions after at least a year of cultivation a H. alba (North Fork Mountain, WV; Folk 63 [deposited at OS]) b H. pubescens (Pilot Mountain, NC; Folk 96 [deposited at OS]) c Heuchera × hispida (=H. americana var. hispida; near Sandstone Falls, WV; Folk 104 [deposited at OS]) d H. americana var. americana (Blue Ridge Parkway at Twenty Minute Cliff, VA; Folk 102 [deposited at OS]). Images e–h H. alba plants growing at North Fork Mountain, WV (e, g) and Shikellamy State Park, PA (f, h). All photos R. Folk, except (f) and (h) by C. Martine.
Figure 1 from: Schuette S, Folk RA, Cantley JT, Martine CT (2018) The hidden Heuchera: How science Twitter uncovered a globally imperiled species in Pennsylvania, USA. PhytoKeys 96: 87-97. https://doi.org/10.3897/phytokeys.96.23667
Figure 1 Range extent of Heuchera alba and Heuchera pubescens in the Appalachian Ridge and Valley. Orange circles indicate range and location of H. alba in WV and VA; Blue circles indicate partial range and location of H. pubescens; Orange crosses represent new locations of H. alba in Pennsylvania.
Dallilar 2017 Science Data Share
<p>Data share for: http://science.sciencemag.org/content/358/6368/1299</p>
Figure 3 from: Magnussen T, Søli GEE, Kjærandsen J (2019) Allodia Winnertz from the Himalayas, with nine species new to science (Diptera, Mycetophilidae). ZooKeys 820: 119-138. https://doi.org/10.3897/zookeys.820.31618
Figure 3 Gonostyli from inner side. AAllodiahimalayensisBAllodianepalensisCAllodiathudamensisDAllodiascalprata. Red arrow indicates the absence of a caudally projecting process of the internal lobe.
Figure 2 from: Magnussen T, Søli GEE, Kjærandsen J (2019) Allodia Winnertz from the Himalayas, with nine species new to science (Diptera, Mycetophilidae). ZooKeys 820: 119-138. https://doi.org/10.3897/zookeys.820.31618
Figure 2 Gonostyli from inner side. AAllodiacaligataBAllodiadiboliaCAllodiashimaiDAllodiaspathulataEAllodiahorologia. Abbreviations: b par = basal part, d lb = dorsal lobe, int par = internal part, m lb = median lobe, v lb = ventral lobe. Red arrow indicates the caudally projecting process of the internal lobe.
Figure 1 from: Magnussen T, Søli GEE, Kjærandsen J (2019) Allodia Winnertz from the Himalayas, with nine species new to science (Diptera, Mycetophilidae). ZooKeys 820: 119-138. https://doi.org/10.3897/zookeys.820.31618
Figure 1 Allodiacaligatasp. n. A habitus B genital capsule, ventral view C genital capsule, dorsal view. Abbreviations: b par = basal part, d lb = dorsal lobe, hyp lb = hypandrial lobe, int par = internal part, m lb = median lobe, tg = tergite.
Citizen science meets integrated taxonomy to uncover the diversity and distribution of Corallimorpharia in Singapore
<p>Phylogenetic datasets and trees</p>
Figure 5 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
Figure 5 Dorsal pictures of the species of Galerucinae – Alticini from El Salvador currently present in the collections of the RBINS. Pictures of nomina nuda spec.s are not depicted. AAcallepitrixestebaniaBAlagoasaacutangulaCA.bipunctataDA.ceracollisEAyalaiaminorFA.salvadorensisGCacoscelisguazapaHChaetocnemafulvicornisIC.mexicanaJChalatenanganyaquadrifidaKCyrsylusrecticollisLDeuteralticalongicornisMDiphalticatrifiniensisNDiphaulacacordobaeOD.wagneriPDisonychabrevilineataQD.figurataRD.nigritaSD.ovataTD.recticollisUEpitrixhirtulaVGenaphthonatransversicollisWLongitarsusberryiXL.varicornisYLupraeafulvicollisZL.portilloiaMacrohalticasalvadorensisbOreinoderaapteracPhrynocephalaevicollisdPhysimerusfemoralisePlatiprosopusacutangulusfPlectotetrasurquiagSyphreabalneriahS.pretiosaiS.quintanillaijSystenavariabiliskWalterianellavenustula. High resolution images can be found at http://collections.naturalsciences.be/ssh-entomology.
Figure 3 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
Figure 3 Dorsal pictures of the species of Chrysomelinae from El Salvador currently present in the collections of the RBINS. ACalligraphabajulaBC.fulvipesCC. (Zygospila) championiDC. (Zygospila) guttulosaEC. (Zygospila) piceicollisFC. (Zygospila) signatipennisGLeptinotarsaundecimlineata. High resolution images can be found at http://collections.naturalsciences.be/ssh-entomology.
Figure 4 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
Figure 4 Dorsal pictures of the species of Eumolpinae from El Salvador currently present in the collections of the RBINS. Pictures of nomina nuda spec.s are not depicted. ABrachypnoeacretiferaBB.lateralislateralisCB.lefeivreilefeivreiDB.viridisEChalcophanacinctaFChrysodinopsiscupricepsGColaspisfreyiHC.inconstansIC.lebasiJEumolpusrobustusKNodocolaspisimpressaLPrionoderahirtipennisMSpintherophytacoruscaNTalurusrugosusOTypophoruslimbatusPTypophorusmexicanusQTypophorusnigritusobliquus var. a RTypophorusnigritusobliquus var. b STypophorusnigritusobliquus var. c. High resolution images can be found at http://collections.naturalsciences.be/ssh-entomology.
Figure 2 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
Figure 2 Dorsal pictures of some of the species of Cassidinae from El Salvador from the collections of the RBINS. AChalepussimulatusBEuprionotagebieniCOcthispaatroterminataDSumitrosisdistinctusESumitrosisfryiFUroplatasculptilis. High resolution images can be found at http://collections.naturalsciences.be/ssh-entomology.
Figure 1 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
Figure 1 Heatmap of the species recorded per department of El Salvador. The darker the colour, the more species have been recorded. Numbers between brackets indicate number of species (first number) and number of genera (second number): (Species / Genera).
Supplementary material 1 from: Van Roie M, De Wint F, Güngor A, Huyghe C, Dekoninck W, Sekerka L (2019) An annotated checklist of the leaf beetles (Coleoptera, Chrysomelidae) from El Salvador, with additions from the Bechyné collection in the Royal Belgian Institute of Natural Sciences. In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 137-196. https://doi.org/10.3897/zookeys.856.32017
: Data type: species data
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)
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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.