説明
Data from IBAN detailing sampling event data on human observations of insects of the order Lepidoptera collected by citizen and amateur scientists in three countries, using the pollard walk method for the purposes of monitoring occurrence of Lepidoptera species.
The data were digitized and cleaned and presented here in Darwin Core format for research purposes.
データ レコード
この サンプリング イベント 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、197 レコードが含まれています。
拡張データ テーブルは2 件存在しています。拡張レコードは、コアのレコードについての追加情報を提供するものです。 各拡張データ テーブル内のレコード数を以下に示します。
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。
バージョン
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。
引用方法
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。:
https://docs.gbif.org/course-data-mobilization/en/scenario-3.html http://slides.com/dimitribrosens/o-3#/17
権利
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 Training Organization。 This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.
GBIF登録
このリソースをはGBIF と登録されており GBIF UUID: 0f96526e-ef16-4e1a-87c3-11c1e015e9f8が割り当てられています。 GBIF Secretariat 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Training Organization が、このリソースをパブリッシュしました。
キーワード
Samplingevent Lepidoptera HumanObservation
連絡先
- データ利用者
- Curator of Entomology
- Corner Park and Leopold Takawira Bulawayo Zimbabwe
- +263772933071
- データ利用者
- Administration
- Corner Park and Leopold Takawira Bulawayo Zimbabwe
- +263772933071
地理的範囲
31.0461° N, 34.8516° E
座標(緯度経度) | 南 西 [-90, -180], 北 東 [90, 180] |
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プロジェクトデータ
The International Butterfly Amateur Network (IBAN) has been providing a framework for national amateur observational groups to capture data about the occurrence of butterflies (Lepidoptera) since 2009. An extensive network of amateur observers use a standard protocol based on Pollard walks to capture this information on paper sheets that they send to their national office. Some of these offices digitize this information into spreadsheets, but others do not have the human resources to do this and they send the paper logs to the IBAN for processing. IBAN produces an annual report based on the sightings provided by these national members, with updated distribution maps and analysis of population trends for some key species. The IBAN headquarters is mainly staffed with volunteers. With the increasing popularity of citizen science and the general interest in butterflies as a charismatic group of organisms, more and more data are received every year and the paper data sheets quickly pile up undigitized. The IBAN steering committee is trying to identify a more efficient and agile workflow for the creation of digital data because they would like to start publishing these data online regularly. They would also like to start processing digital pictures that their volunteers are already capturing with mobile devices like phones and tablets. Their ultimate objective is to raise the profile of the network and strengthen collaborations with local and regional governments to influence conservation policies for Lepidoptera in the countries involved. There is currently no formal agreement between IBAN and the amateurs capturing data, to cover the ways in which the data can be used, for example. The steering committee has some concerns that when they start publishing the data online, they will have to formalize this arrangement.
タイトル | Sampling of Lepidoptera across Countries |
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識別子 | Monitoring project |
研究の意図、目的、背景など(デザイン) | The IBAN headquarters is mainly staffed with volunteers. With the increasing popularity of citizen science and the general interest in butterflies as a charismatic group of organisms, more and more data are received every year and the paper data sheets quickly pile up undigitized. The IBAN steering committee is trying to identify a more efficient and agile workflow for the creation of digital data because they would like to start publishing these data online regularly. They would also like to start processing digital pictures that their volunteers are already capturing with mobile devices like phones and tablets. Their ultimate objective is to raise the profile of the network and strengthen collaborations with local and regional governments to influence conservation policies for Lepidoptera in the countries involved. There is currently no formal agreement between IBAN and the amateurs capturing data, to cover the ways in which the data can be used, for example. The steering committee has some concerns that when they start publishing the data online, they will have to formalize this arrangement. Data collection The recommended protocol —Pollard walks— is based on transects that range between 300 and 600 m in length, divided into 50 m sections. Each transect should cover a single habitat type. In each visit, transect-walkers have to count all species of Lepidoptera that can be seen within 5 m of the transect line. Special behaviours (egg laying or nectaring), as well as developmental stage (e.g., larvae or eggs), should be recorded as well. For most countries, these sampling efforts happen once every two weeks from the beginning of October to the end of June. There are quality control measures in place: every reported record is flagged "Pending approval". Record status is only changed to "Approved" after verification by a designated taxonomic expert. Species spotted out of their regular season or distribution area are flagged for additional verification. Time of day and weather conditions are recorded at the beginning of the transect. Along the transect, the number of individuals of every species seen is counted. Un-identified species are counted and recorded either by family or as a predefined complex of two or three similar species. Butterflies seen outside the 5 meter range are recorded as “Extra+the number of the nearest section” (e.g. 5-extra). The end time of the transect is also recorded. |
プロジェクトに携わる要員:
- キュレーター
- データ公開者
収集方法
The recommended protocol —Pollard walks— is based on transects that range between 300 and 600 m in length, divided into 50 m sections. Each transect should cover a single habitat type. In each visit, transect-walkers have to count all species of Lepidoptera that can be seen within 5 m of the transect line. Special behaviours (egg laying or nectaring), as well as developmental stage (e.g., larvae or eggs), should be recorded as well. For most countries, these sampling efforts happen once every two weeks from the beginning of October to the end of June. There are quality control measures in place: every reported record is flagged "Pending approval". Record status is only changed to "Approved" after verification by a designated taxonomic expert. Species spotted out of their regular season or distribution area are flagged for additional verification. Time of day and weather conditions are recorded at the beginning of the transect. Along the transect, the number of individuals of every species seen is counted. Un-identified species are counted and recorded either by family or as a predefined complex of two or three similar species. Butterflies seen outside the 5 meter range are recorded as “Extra+the number of the nearest section” (e.g. 5-extra). The end time of the transect is also recorded.
Study Extent | Ongoing monitoring study on Lepidoptera. Once evert 2 weeks October to June annually |
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Quality Control | The Excel file sheet for event data was converted to CSV and uploaded onto open refine. Sample size value column was queried under text facet and 2 entries popped up either 250 square meters or blank, the blank entries were changed to 250. Event date column, text facet and physical dates checked, two columns had format inconsistent with the rest 23-02-2011 was changed to 23-02-11 Verbatim locality went through the text facet option and revealed spelling errors (botanik in Jerusalem Givat-ram botanik garden, changed to botanic), (grazing in Ramat hanadiv griga without graziing changed to grazing and capital H and G added) (botanik in Jerusalem Givat-ram botanik garden changed to botanic) The cluster function was used on the same column and no clusters were worth merging. Spelling change sheve to sheva Text facet the decimal latitude column and it revealed inconsistency; Kfar aza has the same coordinate as 31.4875 and 31.48747222, the latter is consistent with the bulk of the records on the column so the shorter version was changed into the longer one. Three coordinates found for Jerusalem bird research station 31.7793, 31.77946667, and 31.77968333. Google maps gave this latitude and longitude in decimal degrees 31.779341028171853, 35.20615792566817, hence all three were edited to this latitude 31.77934103 One coordinate was given in QDS as 32 32 40.2 N 34 56 22.6 E, this was converted to decimal degrees using canadensys coordinate converter to lat 32.5445, and long 34.9396111. Beer sheve andartat hanegev name changed to Beer sheva andartat hanegev, had no coordinates recorded, so Geolocate was used to find the decimal degree coordinates which were 30.5 lat, and 34.916667 long, Google maps gave 31.266747122677355, 34.82062005448895. The Occurrence data file was also added into open refine as a csv file. In Openrefine reconciled the scientific name column The speciesName column had a mixture of all taxonomic ranks in one column and once flagged the resolution is to create separate columns for other ranks. The species name column was copied and pasted into GBIF name parser and the result was analyzed to separate different ranks and fill out the taxonomic gaps. These gaps were filled by searching the GBIF website, Global names index, Discover Moths as well as Google search, at the same time verifying spellings. Changes were made in open refine. The coordinates column was checked for inconsistencies and format, the blank columns were filled in from Geolocate Georeference calculator, the accuracy for the decimal degree coordinates was cut down to 4 and the QDS coordinate was changed to decimal degrees in canadensys. These results were updated in openrefine The cleaned coordinates were plotted as a separated cvs file on Google maps to verify if they were located in Israel the country of study. |
Method step description:
- Global Names Index, name parser API to check for taxonomic consistency. The speciesName column had a mixture of all taxonomic ranks in one column and once flagged the resolution is to create separate columns for other ranks. Catalogue of life and GBIF database as well as Discover Moths helped verify the taxonomic hierarchies. Open refine in open refine I can maneuver the data more easily by flagging duplications and inconsistencies in spelling, data that is out of range (dates) and also the accuracy of coordinates so they can be to the same decimal points. Google Maps helped to check if the coordinates fell within the specified study area. Geolocate helped fill in blank spaced in the latitude and longitude columns Canadensys co-ordinate coordinator helps with converting a QDS coordinate that was not converted into Decimal degrees Canadensys can also help with date parsing, for the date column. In Open refine the reconcile function was meant to assist with the scientificName column but I couldn’t get it to work, so this was done manually through facet and cluster
書誌情報の引用
- Chapman, A. D. (2005). Principles and methods of data cleaning. GBIF. https://books.google.co.zw/books?id=44gDJTEJoVIC&lpg=PA1&ots=vThW46i8ur&dq=arthur%20d%20chapman%20principles%20and%20methods%20of%20data%20cleaning&lr&pg=PA1#v=onepage&q=arthur%20d%20chapman%20principles%20and%20methods%20of%20data%20cleaning&f=false
追加のメタデータ
目的 | This data was uploaded for training purposes. |
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代替識別子 | 0f96526e-ef16-4e1a-87c3-11c1e015e9f8 |
https://training-ipt-c.gbif.org/resource?r=lepidoptera-sampling-event-uc2_madamba |