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S92 | FLUOROPHARMA | List of ~340 ATC classified fluoro-pharmaceuticals
<p>This is the collection associated with list S92 FLUOROPHARMA, List of ~340 ATC classified fluoro-pharmaceuticals on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p> </p> <p>A list of ~340 fluoro-pharmaceuticals classified as per WHO'S Anatomical Therapeutic Chemical (ATC) classification based on their medical application, described in Inoue et. al. DOI: <a href="https://pubs.acs.org/doi/10.1021/acsomega.0c00830">10.1021/acsomega.0c00830</a> </p> <p>Structural identifiers and mapping to DTXSID, CASRN provided by ECI. v0.1.1: removed three non-F containing entries (CIDs 1061, 5360545, 56603655) and added information for CID 3039780. </p>
S10 | SWISSPHARMA | Pharmaceutical List with Consumption Data
<p>This is the collection associated with list S10 SWISSPHARMA on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S10 | SWISSPHARMA | <strong>Pharmaceutical List with Consumption Data</strong></p> <p>Table S2 from Singer <em>et al.</em> 2016. DOI: <a href="http://pubs.acs.org/doi/abs/10.1021/acs.est.5b03332">10.1021/acs.est.5b03332</a></p> <p>2024: added consumption data and mappings file for PubChem. </p>
The data for "Accurate Infrared Line Lists for 20 Isotopologues of Carbon Disulfide (CS2) at Room Temperature"
<p>[<strong>Updates on 2025-03-02</strong>: energy levels and line lists of CS2 323 and 333 isotopologues are corrected; energy levels of 224, 223, and 232 isotopologues are extended to 0.1 au (ZPE included); partition function (Q) of first 4 isotopologues by direct summation up to 4000 K; number of 323 and 333 iso lines in natural line list are updated; natural line lists are updated]</p> <p>The paper was published online at <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ad3809">ApJS</a> with open access to public, DOI: 10.3847/1538-4365/ad3809</p> <p>First-generation data product and IR line lists for Carbon Disulfide (CS2), including an isotopologue-independent <em>ab initio</em> PES of Carbon Disulfide refined with selected HITRAN energy levels below 7000 cm-1, an <em>ab initio </em>DMS fitted with CCSD(T)/aug-cc-pV(T/Q/5+d)Z dipoles computed up to 20,000 cm-1 above potential minimum and extrapolated to one-electron basis set limit, room temperature IR line lists for 20 individual isotopologues of 12/13C and 32/33/34/36S, denoted Ames-296K, and a "natural" CS2 list with intensities scaled by their terrestrial abundances. This project is funded by NASA Grant 18-2XRP18_2-0046 through NASA/SETI Institute Co-operative Agreement 80NSSC19M0121. See https://huang.seti.org/CS2/cs2.html for data format and abundance information. Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. The line profile parameters and room temperature simulations are supported through 80NSSC20K1596.</p> <p><strong>List of Files</strong>, supplement to article " Accurate IR Line Lists for CS2 and Isotopologues at Room Temperature"</p> <ol> <li>Ames-1.PES.zip: Ames-0 and Ames-1 PES subroutine & coefficient files;<br>PES.refinement.files.zip: PES refinement related files including reference energy level list and refinement output.</li> <li><em>J</em>=0-200 energy level lists of 12C32S2 and 19 minor isotopologues, computed on the Ames-1 PES. The .zip file contains 20 compressed .tgz (or .xz) files, and partition function of 222, 224, 223, and 232 isotopologues.</li> <li>Ames-1.DMS.zip: Ames-1 DMS subroutine & coefficient files, and <em>ab initio</em> data;</li> <li>cs2.xxx.Ames-1.296K.1E-31.dat.tgz (or .xz) : 20 files, "xxx" is the S-C-S isotope mass unit number. These are the Ames-296K IR line lists for 12C32S2 and 19 minor isotopologues, each with 100% abundance. Computed using Ames-1 DMS and rovibrational wavefunctions for those energy levels acquired on Ames-1 PES;</li> <li>cs2.20iso.Ames.natural.296K.1E-31.10Kcm-1.dat.updated.tgz: A "natural" Ames-296K IR line list for CS2, including 10,018,977 transitions from all 20 isotopologues with their 296K intensities scaled by terrestrial abundances, covering the range of 0 - 10,000 cm-1. Computed on the Ames-1 PES and DMS.</li> <li>cs2.222.A+I.296K.ames+heff.natural.tgz: A(mes)+I(AO).296K line list for the main isotopologue 222, with terrestrial abundance. Ames-296K intensity prediction is combined with the more accurate energy levels (and line positions) from Effective Hamiltonian model.</li> <li>cs2.iso2-20.Ames-1.natural.1E-31.dat.iso2-4_use_HITRAN2020_purified.v5.xz: the Ames "natural" line list for minor isotopologues #2 - #20, in which the energy levels of 224, 223 and 232 are replaced with reliable values in HITRAN2020. Therefore, the final composite line list = 6) + 7)</li> <li>Heff.and.HITRAN.energy.level.matches.and.line.list.update.zip: the short FORTRAN programs for energy level matches between Ames-1 PES levels and Heff model levels, and the subroutines to use Heff and HITRAN energy levels and line positions. Lists of matched Ames vs HITRAN/H_eff levels are also included.</li> <li>ORIGIN project file for related analysis and figures. Use Origin Viewer to open on PC and MAC, <a href="https://www.originlab.com/viewer/dl.aspx">https://www.originlab.com/viewer/dl.aspx</a></li> <li>a Python program to generate line-broadening parameters for rovibrational CS2 molecule</li> <li>CS2 cross-section data of PNNL, HITRAN and Ames line lists. </li> </ol> <p><strong> # Iso #Lines #in"natural" abundance </strong><br> 1 222 1,903,882 1,856,648 0.892811 <br> 2 224 3,983,009 2,159,579 0.0792103 <br> 3 223 3,745,299 1,328,631 0.0140944 <br> 4 232 1,925,377 658,645 0.100306 <br> 5 424 1,940,490 439,254 1.207E-3 <br> 6 234 4,211,645 698,654 8.151E-4 <br> 7 324 3,671,708 589,323 6.510E-4 <br> 8 226 4,155,423 558,540 3.566E-4 <br> 9 233 3,918,753 410,542 1.439E-4 <br>10 323 1,937,950 290,799 5.142E-5 <br>11 434 2,080,912 138,209 1.692E-5 <br>12 426 3,852,415 223,268 1.976E-5 <br>13 334 4,062,765 172,858 6.773E-6 <br>14 236 4,742,198 158,941 4.630E-6 <br>15 326 4,113,292 137,128 3.075E-6 <br>16 333 1,988,991 80,862 6.803E-7 <br>17 436 4,434,008 58,478 1.361E-7 <br>18 626 1,986,823 21,692 3.572E-8 <br>19 336 4,613,173 32,681 3.528E-8 <br>20 636 2,194,332 4,245 4.28E-10 </p> <p><strong>Line List Data Format: </strong>(CS2 is the 53rd molecule in HITRAN, we use iso# from table below, e.g., 1 - 222; 2 - 224; ...; 10 - 323; ....; 20 - 636)</p> <ol> <li>in the original line list files: cs2.xxx.Ames-1.296K.1E-31.dat<br>iso wavenumber S(Ames) A21(Ames) E"(cm-1) <em>v1v2l2v3' v1v2l2v3" JPS' #root' JPS" #root" J' J" e/f</em>_symmetry<br> 2 6.165375 1.492856E-30 4.851961E-12 876.91172 0 2 2 0 0 2 2 0 29 1 2 4 28 2 2 4 29 28 e e</li> <li>in cs2.iso2-20.Ames-1.natural.1E-31.dat.iso2-4_use_HITRAN2020_purified.v5, original Ames-1 line position and the difference = Heff - Ames are appended to the end of each line of iso #2 (224), iso #3 (223), and iso #4 (232). </li> <li>in cs2.222.AI-296K.ames+heff.natural.dat.v2, two integers are added to each line to keep the record for the number of cycles after which a match (or no match) was made for upper and lower levels, "0-41" for "matched", '99' for "not matched", "-1" for out of range, i.e. > 9000 cm-1. The differences between the original Ames and corrected/replaced transition wavenumber, E', and E" are also appended at the end. The relation is wv/E'/E" (Heff) + diff = wv/E'/E" (Ames). For example, in the transition below, E''(Ames) = 3445.4018+0.7865 = 3446.1883 cm-1. <br><em> 1 36.666580 1.538246E-31 2.306988E-07 3445.40177 0 4 2 1 1 6 2 0 57 1 2 31 58 2 2 34 57 58 e e 3 3 -0.7207 0.0658 0.7865</em></li> </ol> <p> </p>
S94 | FLUOROPEST | List of 423 FRAC/HRAC/IRAC classified fluoro-agrochemicals
<p>This is the collection associated with list S94 FLUOROPEST, List of 423 FRAC/HRAC/IRAC classified fluoro-agrochemicals on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>A list of 423 Fungicide Resistance Action Committee (FRAC), Herbicide Resistance Action Committee (HRAC) or Insecticide Resistance Action Committee (IRAC) classified fluoro-agrochemicals based on their chemotype and mode of action , described in Ogawa et al DOI:<a href="https://doi.org/10.1016/j.isci.2020.101467">10.1016/j.isci.2020.101467</a> </p> <p>Structural identifiers and mapping to DTXSID, CASRN provided by ECI.</p>
S25 | OECDPFAS | List of PFAS from the OECD
<p>This is the collection associated with list S25 OECDPFAS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S25 | OECDPFAS | <strong>List of PFAS from the OECD</strong></p> <p>A list of PFAS released by the OECD, provided by Zhanyun Wang. Details in this <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/ENV-JM-MONO%282018%297.pdf">OECD Monograph</a>. Extensive registration and curation performed by CompTox Dashboard team (see CompTox files). </p> <p>Nov 14 update: added CSV. Feb 6, 2020: minor SMILES corrections in CSV for PubChem upload. 12 Mar 2022: corrected structure for DTXSID90703694.</p>
A list of items in the FAIRsFAIR training library
<p>A file containing a list of items, with basic metadata, that were included in the <a href="https://www.fairsfair.eu/competence-centre/training-library">FAIRsFAIR training library</a> </p> <p> </p>
S95 | PFASANEXCH | PFAS List from the NORMAN PFAS Analytical Exchange Activity
<p>This is the collection associated with list S95 PFASANEXCH on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>This is a list from the <a href="https://www.norman-network.net/sites/default/files/files/QA-QC%20Issues/2021%20NORMAN%20network%20PFAS%20Analytical%20Exchange%20Final%20Report%2014022022.pdf">PFAS Analytical Exchange Activity</a>, part of NORMAN Joint Programme of Activities (JPA) 2021 coordinated by UK Environment Agency. This activity aimed to gain an understanding of the current analytical capability of PFAS as Limit of Detection (LOD) in participating international laboratories.</p>
S27 | KWRSJERPS2 | Extended Suspect List from Sjerps et al (KWRSJERPS)
<p>This is the collection associated with list S27 KWRSJERPS2 on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S27 | KWRSJERPS2 | <strong>Extended Suspect List from Sjerps<em> et al</em> (KWRSJERPS)</strong></p> <p>Table S4 from Sjerps <em>et al</em>. 2016 Water Research 93: 254-264. </p> <p>DOI: <a href="http://www.sciencedirect.com/science/article/pii/S0043135416300938">10.1016/j.watres.2016.02.034</a>.</p> <p>14 Nov update: added CSV extract of docx. 29/4/2022 update: added missing InChIKey file.</p>
S6 | ITNANTIBIOTIC | Antibiotic List: ITN MSCA ANSWER
<p>This is the collection associated with list S6 ITNANTIBIOTIC on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S6 | ITNANTIBIOTIC | <strong>Antibiotic List: ITN MSCA ANSWER</strong></p> <p>A list of antibiotics compiled by Nikiforos Alygizakis (EI/Uni Athens), see e.g. Paulus <em>et al</em> 2019 DOI: <a href="https://doi.org/10.1016/j.ijheh.2019.01.004">10.1016/j.ijheh.2019.01.004</a></p> <p>Suspect list of human phase-I antibiotic metabolites, created with <a href="https://biotransformer.ca/">BioTransformer</a> (v3.0.0) provided by Tim Jonkers (VU, NL). Jonkers <em>et al</em> (in prep.)</p> <p>v0.2.0: added the CYP Metabolites Step 1 files.</p>
A list of newly (re)appearing alien species in Belgium in support of decision making
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a workflow based on FAIR principles to identify new species in Belgium. These are species that have been newly observed on the territory or that were newly added to a species registry or checklist. The workflow is built on the Global Biodiversity Information Facility (GBIF) and uses the Belgian Global Register of Introduced and Invasive Species (<a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">GRIIS Belgium</a>) as a baseline for comparison. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/06_occurrence_indicators_appearing_taxa.html" target="_blank" rel="noopener">pipeline</a> that generates a list of new alien species occurring in Belgium. This pipeline retrieves alien taxa from openly published species checklists or occurrence datasets on GBIF and compares this list with the <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG). This register is based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow. Appearing/reappearing species are defined as follows:</p> <ul> <li>Appearing: an alien species which newly occurs on the Belgian territory in the three years before the year of the GBIF download used for creating the <a href="../records/10527772" target="_blank" rel="noopener">occurrence cube for non-native taxa in Belgium</a>. We will refer to this 3 years period as <em>evaluation period</em>.</li> <li>Re-appearing: an alien species reappearing on the Belgian territory after a latency of 4 years or more. For example, we consider a taxon reappearing in 2022 if observations occur in 2022 and 2018 or before.</li> </ul> <h2><strong>Files</strong></h2> <ul> <li><code>appearing_taxa.tsv</code></li> <li><code>reappearing_taxa.tsv</code></li> </ul> <h2><strong>Field values</strong></h2> <p>Field values of <code>appearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of appearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species occurs for the first time in protected areas of NATURA2000 in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species occurs for the first time in Belgium during the evaluation period(<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <p>Field values of <code>reappearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of reappearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species reappears in protected areas of NATURA2000 in Belgium (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species reappears in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>n_latent_years</code>: latency, in year, i.e. the number of years since last occurrence in Belgium</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <h2><strong>Potential uses of the dataset</strong></h2> <p>The list of newly (re)appearing alien species in Belgium can be used for various purposes:</p> <ul> <li>to update the Belgian GRIIS checklist</li> <li>to flag the occurrence of new, regulated species on the territory (early warning)</li> <li>to develop a rapid response </li> <li>to select species for quick impact assessment</li> <li>to select species for risk assessment</li> <li>to draft alert lists</li> <li>for horizon scanning alien species</li> <li>to select species for risk assessment</li> <li>to identify new introduction patways</li> <li>...</li> </ul>
Prioritized lists of alien species in Belgium and its regions
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a <a href="https://trias-project.github.io/indicators/" target="_blank" rel="noopener">indicator workflow</a> based on FAIR principles to feed <strong>policy relevant indicators for biological invasions in Belgium</strong> from openly published checklist and occurrence data on GBIF. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html">pipeline</a> that prioritizes alien species based on their emergence status. This prioritization is built upon the information contained in:</p> <ul> <li> The <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG) based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow.</li> <li>The <a href="../records/10527772" target="_blank" rel="noopener">species occurrence cube for non-native taxa in Belgium</a>.</li> </ul> <p>We provide two different prioritization strategies: hierarchical ranking and point strategy.</p> <p>We do the prioritzation for both Belgium and its three regions separately: Flanders, Wallonia and Brussels. Only the prioritization for Belgium takes into account the emergence status (number of occurrences and observed occupancy) in Natura2000 protected areas.</p> <h3>Hierarchical ranking</h3> <p>The ranking is based on the highest emerging status. The following priority rules are applied, in order of importance:</p> <ol> <li>The more recent, the higher priority is.</li> <li>Emerging statuses in protected areas are more important than the ones defined over entire Belgium.</li> <li>Emerging statuses from occupancy are more important than the ones from occurrences.</li> <li>The higher average minimal guaranteed growth (#occs/year), the higher priority is.</li> </ol> <h3>Points strategy</h3> <p>The points strategy is based on applying gain factors to emerging statuses using the number of observations in 2020 in Belgium/region as reference (gain factor = 1). The gain factor tables for both Belgium and its regions are available in the <a title="pipeline" href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html#42_Point_strategy">pipeline</a>.</p> <h2><strong>Files</strong></h2> <ul> <li><code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Brussels.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Brussels.tsv</code></li> </ul> <h2>Field values</h2> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region * in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>* </strong>in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 72</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 31.5</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the regin <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul>
Listing of data repositories that embed schema.org metadata in dataset landing pages
<p>Machine-readable metadata available from landing pages for datasets facilitate data citation by enabling easy integration with reference managers and other tools used in a data citation workflow. Embedding these metadata using the schema.org standard with the JSON-LD is emerging as the community standard. This dataset is a listing of data repositories that have implemented this approach or are in the progress of doing so.</p> <p>This is the first version of this dataset and was generated via community consultation. We expect to update this dataset, as an increasing number of data repositories adopt this approach, and we hope to see this information added to registries of data repositories such as re3data and FAIRsharing.</p> <p>In addition to the listing of data repositories we provide information of the schema.org properties supported by these data repositories, focussing on the required and recommended properties from the "Data Citation Roadmap for Scholarly Data Repositories".</p>
S5 | KWRSJERPS | KWR Drinking Water Suspect List
<p>This is the collection associated with list S5 KWRSJERPS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S5</p> <p>KWRSJERPS</p> <p><strong>KWR Drinking Water Suspect List</strong></p> <p>KWR Suspects <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/NormanTargetSuspects-KWR_withStruct_DTXSIDs.csv">CSV</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/NormanTargetSuspects-KWR_withStruct_DTXSIDs.xlsx">XLSX</a> (3/10/2017)</p> <p>CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/kwrsjerps">KWRSJERPS List</a></p> <p><a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/NormanTargetSuspects-KWR_InChIKeys.txt">KWR InChIKeys</a> (15/03/2016)</p> <p>Sjerps <em>et al</em>. 2016 Water Research 93: 254-264. <br> DOI: <a href="http://www.sciencedirect.com/science/article/pii/S0043135416300938">10.1016/j.watres.2016.02.034</a></p>
S4 | UJIBADE | University of Jaume I Bade et al List
<p>This is the collection associated with list S4 UJIBADE on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S4</p> <p>UJIBADE</p> <p><strong>University of Jaume I</strong></p> <p>Bade <em>et al </em><a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/Bade_etal_544Compounds_wInChIs_DTXSIDs.csv">CSV</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/Bade_etal_544Compounds_wInChIs_DTXSIDs.xlsx">XLSX</a> (3/10/2017)</p> <p>CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/ujibade">UJIBADE List</a></p> <p><a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/Bade_etal_2015_544Compounds_InChIKeys.txt">Bade <em>et al</em> InChIKeys</a> (28/11/2015)</p> <p>Bade <em>et al</em> 2015, Sci. Tot. Environ. 538: 934-941. <br> DOI: <a href="http://dx.doi.org/10.1016/j.scitotenv.2015.08.078">10.1016/j.scitotenv.2015.08.078</a> </p>
S40 | ALGALTOX | Algal toxins list from CompTox
<p>This is the collection associated with list S40 ALGALTOX on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S40</p> <p>ALGALTOX</p> <p><strong>Algal toxins list from CompTox</strong></p> <p>ALGALTOX <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/ALGALTOX_14022019.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/ALGALTOX_14022019.csv">CSV</a> (14/02/2019)<br> CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/algaltox">ALGALTOX List</a></p> <p>ALGALTOX <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/ALGALTOX_InChIKeys_14022019.txt">InChIKeys </a>(14/02/2019)</p> <p>List of algal toxins (generated during blooms) from the CompTox Chemicals Dashboard.</p>
S48 | CPPDBLISTA | Database of Chemicals likely (List A) associated with Plastic Packaging (CPPdb)
<p>This is the collection associated with list S48 CPPDBLISTA on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S48 | CPPDBLISTA | <strong>Database of Chemicals associated with Plastic Packaging (CPPdb)</strong></p> <p>CPPdb Original File (List A and B) <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListA_ListB_181009_ZenodoV1.xlsx">XLSX</a> (06/03/2019)<br> Mapped Files (06/03/2019):<br> Table 2 from Groh et al as <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/Table2_Groh_etal_stoten_mapped.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/Table2_Groh_etal_stoten_mapped.csv">CSV</a> <br> CPPdb List A <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListA_Mapped_06032019.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListA_Mapped_06032019.csv">CSV</a> <br> CPPdb List B <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListB_Mapped_06032019.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListB_Mapped_06032019.csv">CSV</a></p> <p>Table 2 Groh et al. <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/Table2_Groh_etal_InChIKeys.txt">InChIKeys</a><br> CPPdb List A <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListA_InChIKeys.txt">InChIKeys</a><br> CPPdb List B <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/CPPdb_ListB_InChIKeys.txt">InChIKeys</a><br> (all 06/03/2019)</p> <p>A database of chemicals likely (List A, 903) and possibly (List B, 3353 - in another upload) associated with plastic packaging, with hazard data, from Groh et al 2019 DOI: <a href="https://doi.org/10.1016/j.scitotenv.2018.10.015">10.1016/j.scitotenv.2018.10.015</a>. Mapped to structures by CAS/Name by K. Groh & E. Schymanski.</p> <p>Latest version of original data (last update Oct 2018): DOI: <a href="http://doi.org/10.5281/zenodo.1287773">10.5281/zenodo.1287773</a></p> <p> </p>
S47 | ECHAPLASTICS | A list from the Plastic Additives Initiative Mapping Exercise by ECHA
<p>This is the collection associated with list S47 ECHAPLASTICS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S47</p> <p>ECHAPLASTICS</p> <p><strong>A list from the Plastic Additives Initiative Mapping Exercise by ECHA</strong></p> <p>Merged ECHA Plastic Additives with Structures <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/ECHA_PlasticAdditivesInitiative_06032019.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/ECHA_PlasticAdditivesInitiative_06032019.csv">CSV</a> (06/03/2019)</p> <p>ECHA Plastic Additives <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/ECHA_Plastics_InChIKeys.txt">InChIKeys</a> (06/03/2019)</p> <p>List with several categories released on <a href="https://echa.europa.eu/mapping-exercise-plastic-additives-initiative">https://echa.europa.eu/mapping-exercise-plastic-additives-initiative</a> and mapped to structures by CAS and Name by E. Schymanski. </p>
S56 | UOATARGPHARMA | Target Pharmaceutical/Drug List from University of Athens
<p>This is the dataset associated with list S56 UOATARGPHARMA on the NORMAN Suspect List Exchange:</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p>
S24 | HUMANNEUROTOX | List of Human Neurotoxins
<p>This is the collection associated with list S24 HUMANNEUROTOX on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S24</p> <p>HUMANNEUROTOX</p> <p><strong>List of Human Neurotoxins</strong></p> <p>Human Neurotoxin List <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/HUMANNEUROTOX-2018-06-19-15-34-35.xls">XLS</a> (19/06/2018)<br> CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/humanneurotox">HUMANNEUROTOX List </a></p> <p>Human Neurotox <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/HUMANNEUROTOX-2018-06-19_InChIKeys.txt">InChIKeys</a> (19/06/2018)</p> <p>A set of chemicals listed as neurotoxicants by Grandjean and Landrigan, DOI: <a href="https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(06)69665-7/fulltext">10.1016/S0140-6736(06)69665-7</a>. List provided by Emma Schymanski/Antony Williams.</p> <p>Nov 14 update: added CSV</p>
S7 | EAWAGSURF | Eawag Surfactants Suspect List
<p>This is the collection associated with list S7 EAWAGSURF on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>Updated 21/11/2019 to contain representative explicit structures for species observed in the 2014 study. Note that for some species multiple isomers are possible; only one representative has been added per formula. Structures created using RChemMass (<a href="https://github.com/schymane/RChemMass/">https://github.com/schymane/RChemMass/</a>)</p> <p>S7: EAWAGSURF: <strong>Eawag Surfactants Suspect List </strong></p> <p>Suspect formulas: <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/Surfactant_Suspects_Schymanski_etal_2014.csv">CSV</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/Surfactant_Suspects_Schymanski_etal_2014.xlsx">XLSX</a></p> <p>CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/eawagsurf">EAWAGSURF List</a></p> <p>Schymanski <em>et al</em>. 2014. DOI: <a href="http://pubs.acs.org/doi/abs/10.1021/es4044374">10.1021/es4044374</a></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.