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The Taiwan Roadkill Observation Network Data Set.

Dataset homepage

Citation

Lin T (2020). The Taiwan Roadkill Observation Network Data Set.. Version 1.5. Taiwan Endemic Species Research Institute. Occurrence dataset https://doi.org/10.15468/cidkqi accessed via GBIF.org on 2021-04-11.

Description

We describe the wildlife road kill data set collected by citizen scientists from the Taiwan Road Observation Network (TaiRON). This data set includes 46,416 geospatially referenced occurrence points of wildlife found on road networks in Taiwan starting in 2011 and until Dec. 2017. These road kill occurrence points come from Taiwan and the main islands that belong Taiwan, an 35,000 km2 island off the Eastern coast of China with high biodiversity and endemism. Each observation includes at least one photo, species name, and date and time of collection, Project managers and group experts identify each photograph and label them with vernacular and scientific names. The labelled observations are collected via an on-line platform, and compiled into a continuously growing dataset of structured records. The data set is still growing as the membership of TaiRON is very active and increasing, with over 14,000 current members. TaiRON and its data set will provide important conservation information about the impacts of human activity and pressures associated with roads on wildlife biodiversity in Taiwan and provides an example of framework that can be replicated elsewhere.

Sampling Description

Study Extent

Taiwan and the main islands that belong Taiwan

Sampling

The volunteers uploaded the photographs of the roadkill victims to the Facebook group from both regular surveys and incidental discoveries.

Quality Control

After experts from the group verified the identification the observation, project managers would review the observation for accuracy and completeness and changed the status of the observation from “unconfirmed” to “confirmed” in the database. All verified data is available for the wider community to access through the website except that of protected species.

Method steps

  1. Stage 1: Crawling Facebook Posts for Occurrence Data to Upload to Database This process was in use from August 2011 to the end of 2015 in which the volunteers posted observation data directly to the Facebook group. Originally, citizen science members uploaded a photo of the road kill specimen with a scale reference directly onto the Taiwan Roadkill Observation Network (Reptile Roadkill Mortality) Facebook page. Pertinent information was included with photos as comments on the published post, including dates, times, species names (if known), and GPS coordinates. We used a web crawler via Facebook’s Graph API to find, retrieve, verify, and input road kill data into the database. The crawler collected posts (along with images, time and location data, and other annotations) on the Facebook Group and put them in an aggregated table of all observations. Participants were also encouraged to collect and send road kill specimens to TESRI. Due to the unstructured format, contributors often did not upload posts with complete information, or did not post pertinent information uniformly, which made crawling for data more difficult. For example, users would often record the location inconsistently, such as decimal degrees or minutes, seconds, degrees format, qualitatively describe the location, post photos of nearby road-side utility poles with locational references, or take screen shots of a GPS app. Soon after launching the web app, TaiRON also released an Android app (“Android App 1.0”) for members on the Android platform to use. Similarly to the TaiRON Web App 1.0, users could submit structured data through the Android app, which would publish uniform information directly through the contributor’s Facebook account. The data would be crawled and verified by project managers before being uploaded to the database. There were several issues in this process. It appeared to encourage users to first publish onto the Facebook group (through Facebook, the TaiRON Web App 1.0, and the TaiRON Android App 1.0). We then crawled the group for data. User and protected species privacy were compromised; and an ever-updating Facebook APIs made application updates to keep up with Facebook necessary. Even though we were able to update the Android app in order to fix bugs that arose when each time Facebook changed its APIs, the Google Play Store’s one week lag-time in releasing the update was prohibitively slow. This prompted the project managers to develop methods to better control the content distributed on the Facebook group and to circumvent Facebook’s constant API updates.
  2. Stage 2: Direct Uploading Observations to Project Website via Android App, and Posting Abridged Information to Facebook Afterwards This process was in use from late 2015 to early 2017. The volunteers posted structured observation records first to the TaiRON project website. The website then posted abridged records to the Facebook group for user interactions and species identifications. Due to the privacy issues and difficulty in keeping up with Facebook’s ever-changing interface, project managers worked with app developers to launch a new version of the free Android app (“Android App 2.0”) that members could download. With the TaiRON Android App 2.0, users were still able to log onto the app through their Facebook account, providing an easy transition for members. The main procedural change this app created was that the app allowed citizen scientists to upload their observations directly to the TaiRON website before the information was published in a uniform manner onto the Facebook group through the contributor’s Facebook account. This effectively resolved issues of gathering non-uniform data with a web crawler for database uploading and added an additional layer for information distribution control. After users uploaded onto the TaiRON website through the app, only the uploader and project managers had access to all the data; the detailed locational data was not published to Facebook. There was also an added option of sending an anonymous observation digest to the Facebook Group. The observer's identity and observation location is kept at the TaiRON website and known by the researchers, but is not available to others at the Facebook Group. This provides some protection of the observer's locational privacy. When the observations are aggregated into datasets, we remove the observers' IDs in the records before the datasets are made available to others. On the other hand, as many participants have opted to release their observation photos under the Creative Commons Licenses, they must be properly attributed when the image files are released. Participants can have photos attributed to their nicknames, or require no attribution at all (by the use of the CC0 Public Domain Dedication). Additionally, this step allowed us to protect the locational data for endangered and protected species, which are not released to the public on the Facebook group or on the project website; users who wished to see this data must be approved by the project managers. Continuing to publish the observations (sans detailed location) to the Facebook group allowed other members, including experts in the group, to have continued involvement in the verification of the data. After experts from the group verified the identification the observation, project managers would review the observation for accuracy and completeness and changed the status of the observation from “unconfirmed” to “confirmed” in the database. All verified data is available for the wider community to access through the website except that of protected species. Though this flip in procedural steps smoothed the process of user data input, data mining/collection from Facebook, and privacy issues with public posts on Facebook, the app was not accessible to members using iOS platforms.
  3. Stage 3: Direct Uploading Observations to Project Website via Web App, and Posting Abridged Information to Facebook Afterwards This process is in use starting from early 2017. The volunteers also posted structured observation records first to the TaiRON project website. This is done by accessing directly to a page at website for uploading observation records. After uploading, the website abridged records to the Facebook group. Because the Apple App Store was prohibitively difficult to publish an app in, and the Android app was often waylaid by the time it took to release new updates, the TaiRON project team has developed the a web-native method (“Web App 2.0”) that is accessible across all smartphone platforms and does not have to be published by a third party app store. Users access the web app through their smartphone’s web browser and TaiRON’s webpage (https://roadkill.tw/). Members sign onto the webpage with their Facebook account and upload through dedicated observation-reporting pages (https://roadkill.tw/app), which is accessible through smartphones, computers, and other mobile devices with Web browsers. Here they have the option to upload up to five photos of an individual, or up to five photos of separate individuals. Once the photos are uploaded, the web app detects date, time, and locational metadata associated with the photo and automatically fills corresponding sections of the form with the option to edit the information. Users can also indicate species, supplementary explanations, if they are sending a specimen, the quantity of individuals observed, and the supposed cause of death. After an observation is directly uploaded to the website by the user, using the Facebook API, the website then automatically publishes the observation sans locational data to Facebook through the group’s user account, “TW Roadkill.” The published Facebook post tags the contributing user to credit them with the observation. After posting in the group, project managers and other expert members can then review the observation for accuracy and completeness, and once verified, change the observation status to “confirmed.” Currently, members can contribute observations to TaiRON’s database through several means, listed in decreasing order of ease of data collection method: 1) TaiRON Web App 2.0 accessed from the mobile website 2) directly posting on the Facebook group, and 3) directly messaging observations to a project manager. Less than 5% of observations are now contributed outside of using the Web App 2.0.

Taxonomic Coverages

We recorded all of the terrestrial vertebrates and land crabs that had be road killed in Taiwan.
  1. Chordata
    rank: phylum
  2. Arthropoda
    rank: phylum
  3. Amphibia
    rank: class
  4. Aves
    rank: class
  5. Malacostraca
    rank: class
  6. Mammalia
    rank: class
  7. Reptilia
    rank: class
  8. Accipitriformes
    rank: order
  9. Anseriformes
    rank: order
  10. Anura
    rank: order
  11. Apodiformes
    rank: order
  12. Artiodactyla
    rank: order
  13. Carnivora
    rank: order
  14. Cetacea
    rank: order
  15. Charadriiformes
    rank: order
  16. Chiroptera
    rank: order
  17. Columbiformes
    rank: order
  18. Coraciiformes
    rank: order
  19. Cuculiformes
    rank: order
  20. Decapoda
    rank: order
  21. Galliformes
    rank: order
  22. Gruiformes
    rank: order
  23. Insectivora
    rank: order
  24. Lagomorpha
    rank: order
  25. Passeriformes
    rank: order
  26. Pelecaniformes
    rank: order
  27. Piciformes
    rank: order
  28. Primates
    rank: order
  29. Rodentia
    rank: order
  30. Squamata
    rank: order
  31. Strigiformes
    rank: order
  32. Testudines
    rank: order
  33. Accipitridae
    rank: family
  34. Aegithalidae
    rank: family
  35. Agamidae
    rank: family
  36. Alaudidae
    rank: family
  37. Alcedinidae
    rank: family
  38. Anatidae
    rank: family
  39. Anguidae
    rank: family
  40. Apodidae
    rank: family
  41. Ardeidae
    rank: family
  42. Bombycillidae
    rank: family
  43. Bovidae
    rank: family
  44. Bufonidae
    rank: family
  45. Campephagidae
    rank: family
  46. Canidae
    rank: family
  47. Caprimulgidae
    rank: family
  48. Cercopithecidae
    rank: family
  49. Cervidae
    rank: family
  50. Cettidae
    rank: family
  51. Charadriidae
    rank: family
  52. Cheloniidae
    rank: family
  53. Ciconiidae
    rank: family
  54. Cisticolidae
    rank: family
  55. Coenobitidae
    rank: family
  56. Colubridae
    rank: family
  57. Columbidae
    rank: family
  58. Corvidae
    rank: family
  59. Cricetidae
    rank: family
  60. Cuculidae
    rank: family
  61. Delphinidae
    rank: family
  62. Dicroglossidae
    rank: family
  63. Dicruridae
    rank: family
  64. Elapidae
    rank: family
  65. Emberizidae
    rank: family
  66. Emydidae
    rank: family
  67. Estrildidae
    rank: family
  68. Felidae
    rank: family
  69. Fringillidae
    rank: family
  70. Gaviidae
    rank: family
  71. Gecarcinidae
    rank: family
  72. Gekkonidae
    rank: family
  73. Geoemydidae
    rank: family
  74. Glareolidae
    rank: family
  75. Grapsidae
    rank: family
  76. Haematopodidae
    rank: family
  77. Herpestidae
    rank: family
  78. Hipposideridae
    rank: family
  79. Hirundinidae
    rank: family
  80. Homalopsidae
    rank: family
  81. Hylidae
    rank: family
  82. Iguanidae
    rank: family
  83. Jacanidae
    rank: family
  84. Lacertidae
    rank: family
  85. Laniidae
    rank: family
  86. Laridae
    rank: family
  87. Leiothrichidae
    rank: family
  88. Leporidae
    rank: family
  89. Manidae
    rank: family
  90. Meropidae
    rank: family
  91. Microhylidae
    rank: family
  92. Miniopteridae
    rank: family
  93. Monarchidae
    rank: family
  94. Motacillidae
    rank: family
  95. Muridae
    rank: family
  96. Muscicapidae
    rank: family
  97. Mustelidae
    rank: family
  98. Ocypodidae
    rank: family
  99. Oriolidae
    rank: family
  100. Paradoxornithidae
    rank: family
  101. Pareatidae
    rank: family
  102. Paridae
    rank: family
  103. Passeridae
    rank: family
  104. Pellorneidae
    rank: family
  105. Phaethontidae
    rank: family
  106. Phasianidae
    rank: family
  107. Phocoenidae
    rank: family
  108. Phylloscopidae
    rank: family
  109. Picidae
    rank: family
  110. Pittidae
    rank: family
  111. Podicipedidae
    rank: family
  112. Potamidae
    rank: family
  113. Procellariidae
    rank: family
  114. Psittacidae
    rank: family
  115. Pycnonotidae
    rank: family
  116. Pythonidae
    rank: family
  117. Rallidae
    rank: family
  118. Ramphastidae
    rank: family
  119. Ranidae
    rank: family
  120. Recurvirostridae
    rank: family
  121. Rhacophoridae
    rank: family
  122. Rhinolophidae
    rank: family
  123. Rostratulidae
    rank: family
  124. Scincidae
    rank: family
  125. Sciuridae
    rank: family
  126. Scolopacidae
    rank: family
  127. Sesarmidae
    rank: family
  128. Soricidae
    rank: family
  129. Strigidae
    rank: family
  130. Sturnidae
    rank: family
  131. Suidae
    rank: family
  132. Sulidae
    rank: family
  133. Sylviidae
    rank: family
  134. Talpidae
    rank: family
  135. Threskiornithidae
    rank: family
  136. Timaliidae
    rank: family
  137. Trionychidae
    rank: family
  138. Troglodytidae
    rank: family
  139. Turdidae
    rank: family
  140. Turnicidae
    rank: family
  141. Typhlopidae
    rank: family
  142. Upupidae
    rank: family
  143. Vespertilionidae
    rank: family
  144. Viperidae
    rank: family
  145. Viverridae
    rank: family
  146. Xenodermatidae
    rank: family
  147. Zosteropidae
    rank: family

Geographic Coverages

Taiwan is a Pacific island roughly 180 kilometres off the south-eastern coast of mainland China. The island was formed by the collision at a convergent boundary between the Philippine Sea Plate and the Eurasian Continental Plate four to five million years ago. Taiwan’s total area is 36,193 km2, and the climate is subtropical in the North to tropical in the South. The data is collected from Taiwan and all the islands that belong Taiwan.

Bibliographic Citations

  1. Tyng-Ruey Chuang, Te-En Lin, Yi-Hong Chang, Chih-Yun Chen, Yu-Kai Chen, Ping-Keng Hsieh, Guan-Shuo Mai. Communal Data Workflow in TaiRON (Taiwan Roadkill Observation Network). In SciDataCon 2016: Advancing the Frontiers of Data in Research. September 11-13, 2016, Denver, Colorado, USA. - http://www.scidatacon.org/2016/sessions/46/paper/129/
  2. Guan‐Shuo Mai, Cheng‐Hsin Hsu, Te‐En Lin, Hsu‐Hong Lin, Dong‐Po Deng, Kwang‐Tsao Shao. Harvesting crowdsourcing biodiversity data from Facebook group. In The 2nd Asian Regional Conference of Society for Conservation Biology. August 07 2012. Biodiversity Research Center, Academia Sinica, Taipei, Taiwan. - https://www.slideshare.net/dongpo/2012-biodiversity-asia-poster
  3. Dongpo Deng, Tyng-Ruey Chuang, Kwang-Tsao Shao, Guan-Shuo Mai, Te-En Lin, Rob Lemmens, Cheng-Hsin Hsu, Hsu-Hong Lin, Menno-Jan Kraak,. 2012. Using social media for collaborative species identification and occurrence: issues, methods, and tools. SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems, ACM. - https://www.researchgate.net/publication/236155410_Using_social_media_for_collaborative_species_identification_and_occurrence_issues_methods_and_tools
  4. Tyng-Ruey Chuang, Dong-Po Deng, Cheng-Hsin Hsu, Lucien C.-H. Lin, Te-En Lin, Guan-Shuo Mai, Kwang-Tsao Shao and Mei-Hsueh Wang. 2015. Collaborative Ecological Observation: Issues in Moving from Social Media to Research Data. In the Citizen Science 2015 Conference. 2015, 11-12 February. San Jose, CA, USA. - https://roadkill.tw/report/27822

Contacts

Te-En Lin
originator
position: Assistant Researcher
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
Telephone: 886-49-2761331ext566
email: mmskink@gmail.com
homepage: http://roadkill.tw
Te-En Lin
metadata author
position: Assistant Researcher
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
Telephone: 886-49-2761331ext566
email: mmskink@gmail.com
homepage: http://roadkill.tw
Dong-Po Deng
programmer
position: Geospatial information specialist
Institute of Information Science, Academia Sinica
128 Academia Road, Section 2 Nangang District 115, Taipei Taiwan
Taipei
115
Taiwan
TW
email: dongpo@iis.sinica.edu.tw
Guan-Shuo Mai
programmer
position: Research Assistant
Biodiversity Research Center, Academia Sinica
128 Academia Road, Section 2 Nangang District 115, Taipei Taiwan
Taipei
115
Taiwan
TW
email: gsmai.taibif@gmail.com
Cheng-Hsin Hsu
programmer
position: Research Assistant
Digital Center, Academia Sinica
128 Academia Road, Section 2 Nangang District 115, Taipei Taiwan
Taipei
115
Taiwan
TW
email: jimshsu@gmail.com
Shih-Wei Chang
processor
position: Associate Research Scientist
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
email: cswei@tesri.gov.tw
Cheng-Te Yao
processor
position: Associate Research Scientist
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
email: yaoct@tesri.gov.tw
Da-Li Lin
processor
position: Assistant Researcher
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
email: thrush1250@gmail.com
Yu-Kai Chen
processor
position: Research Assistant
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
email: waterr37@msn.com
Chih-Yun Chen
processor
position: Research Assistant
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
email: main0516@yahoo.com.tw
Tyng-Ruey Chuang
programmer
position: Associate Research Fellow
Institute of Information Science, Academia Sinica
No 128, Academia Road, Section 2 Nankang, Taipei 11529, Taiwan
Taipei
115
Taiwan
TW
Telephone: 886-2-2788-3799ext1613
email: trcat@iis.sinica.edu.tw
homepage: http://www.iis.sinica.edu.tw/pages/trc/
Jheng-Jhang Li
processor
position: Crustaceans taxonomy specialist
National Museum of Marine Biology and Aquarium
2 Houwan Road, Checheng, Pingtung 944, Taiwan ROC,
Pingtung
944
Taiwan
TW
email: epigrapsus@nmmba.gov.tw
Kristina Chyn
user
position: PH.D. Candidate
Ecology and Evolutionary Biology | Texas A&M University
Wildlife Fisheries & Ecological Sciences (WFES) Rm 267 Texas A&M University College Station, TX 77843
77843
Texas
US
email: kmc365@cornell.edu
homepage: https://kristina-chyn.weebly.com/about.html
Te-En Lin
administrative point of contact
position: Assistant Researcher
Taiwan Endemic Species Researcher Institute
1 Ming-Sheng East Road, Jiji Township, Nantou County, Taiwan
Nantou County
552
Taiwan
TW
Telephone: 886-49-2761331ext566
email: mmskink@gmail.com
homepage: http://roadkill.tw
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