この オカレンス（観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、20,022 レコードが含まれています。

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

DwC-A形式のリソース データまたは EML / RTF 形式のリソース メタデータの最新バージョンをダウンロード：

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

研究者はこの研究内容を以下のように引用する必要があります。:

Simon A, Basman A (2022): Galiano Island BC Canada Marine Zoology 1893–2021. v1.5. Biodiversity Data Journal. Dataset/Occurrence. https://ipt.pensoft.net/resource?r=galiano-data-paper-part-i&v=1.5

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は Biodiversity Data Journal。 This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

このリソースをはGBIF と登録されており GBIF UUID: 56687a3d-b48f-44e5-b2b8-d55bafff2f33が割り当てられています。   Participant Node Managers Committee によって承認されたデータ パブリッシャーとして GBIF に登録されているBiodiversity Data Journal が、このリソースをパブリッシュしました。

Occurrence; Observation; Occurrence

Location: Galiano Island, British Columbia, Canada. For a GeoJSON file precisely designating the study area please see: https://github.com/IMERSS/imerss-bioinfo/blob/8df8a3847aa71e5c28a57f558204ea58e42c15c2/data/Galiano/Galiano_Island_Project_Boundary_Chu_final_2021-02-23.json

Taxonomic groups covered include: Porifera, Cnidaria, Ctenophora, Nemertea, Platyhelminthes, Chaetognatha, Mollusca, Annelida, Sipuncula, Arthropoda, Entoprocta, Brachiopoda, Bryozoa, Phoronida, Echinodermata, Chordata

Over 20,000 marine animal occurrence records from waters around Galiano Island, BC, Canada, dating from 1893 to 2021. Occurrences include dive records collected through the Pacific Marine Life Surveys, museum voucher specimens, ecological data, and crowd-sources observations from the BC Cetacean Sightings Network and iNaturalist platform.

プロジェクトに携わる要員:

Sampling procedures vary according to each data source, including systematic dive records (Pacific Marine Life Surveys), ecological data collected by ROV (Chu and Leys 2010, Chu and Leys 2012), museum voucher specimens (Canadian Museum of Nature, Royal British Columbia Museum), crowd-sourced citizen science observations (British Columbia Cetacean Sightings Network and iNaturalist observations on the Biodiversity Galiano Island Project), and additional reports from the literature (Agassiz 1862, McMurrich 1921, Erickson 2000). Museum specimens may represent collections made through heterogenous methods. All raw catalogues, processing scripts, and processed catalogues contributing to this paper have been tagged in GitHub at https://github.com/IMERSS/imerss-bioinfo/tree/data-paper-i-final .

Method step description:

1. The data catalogues contributing to this dataset have been normalised, aligned, corrected, and rendered into visualisations by a collection of open source data processing scripts written in JavaScript. These scripts operate in the following stages: 1. The columns of each source catalogue, imported as CSV, are mapped onto a common core of fields drawn from a subset of the Darwin Core standard, as well as other project-specific fields 2. The taxon name is mapped onto a core backbone by means of a taxon resolution file which resolves preferred taxon names and accounts for typographical errors 3. A dataset id is assigned to every source catalogue, and they are then combined into a single master catalogue  4. This catalogue is filtered to include only the taxa of interest—marine fauna 5. Private or obscured coordinates held in project-specific fields are copied into the principal georeferencing fields 6. A patch of georeferencing corrections is then applied to the resulting coordinates, together with curational notes motivating the corrections 7. The resulting observations are then filtered by the polygon representing the project area 8. The resulting output produces two consolidated CSV files, a catalogue of all observations, and a master summary file 9. The master summary file is then divided into phyla according to the checklist divisions in this paper, for curation by subject matter experts—these are exported into a Google Sheets representation where they may edit them live 10. The subject matter experts add and check authorities for the taxa, add curation notes and resolve taxonomic discrepancies 11. After curation, the Google Sheets are then re-ingested, combined, and converted back into CSV, and compared with the original summary produced at Step 8 12. Any discrepancies between these summaries are fed into the taxon resolution file at Step 2, and, where appropriate, circulated amongst the managers of the source catalogues to incorporate corrections they find desirable 13. The process is then rerun from Step 1 until repeated passes of curation and reconciliation give rise to no further discrepancies at Step 12 The files output at Step 8 of the pipeline form the basis of the map-based data visualisations referenced from this paper, as well our our Darwin Core data submission to the Global Biodiversity Information Facility.