Biodiversity Information Science and Standards : Conference Abstract
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Conference Abstract
Discovering Known Biodiversity: Digital accessible knowledge — Getting the community involved
expand article infoCarolina Sokolowicz, Marcus Guidoti, Donat Agosti§
‡ Plazi, Porto Alegre, Brazil
§ Plazi, Bern, Switzerland
Open Access

Abstract

Plazi is a non-profit organization focused on the liberation of data from taxonomic publications. As one of Plazi’s goals of promoting the accessibility of taxonomic data, our team has developed different ways of getting the outside community involved. The Plazi community on GitHub encourages the scientific community and other contributors to post GGI-related (Golden Gate Imagine document editor) questions, requirements, ideas, and/or suggestions, including bug reports and feature requests. One can contact us via this GitHub community by creating either an Issue (to report problems on our data or related systems) or a Discussion (to post questions, ideas, or suggestions).

We use Github's built-in label system to actively curate the content posted in this repository in order to facilitate further interaction, including filtering and searching before creating new entries. In the plazi/community repository, there is a Q&A (question & answer) section with selected questions and answers that might help solving the encountered problems.

Aiming at increasing external participation in the task of liberating taxonomic data, we are developing training courses with independent learning modules that can be combined in different ways to target different audiences (e.g., undergraduates, researchers, developers) in various formats. This material will include text, print-screens, slides, screencasts, and, eventually to a minor extent, online teaching. Each topic within a module will have one or more ‘inline tests', which will be HTML form-based with hard-coded answers to directly assess progress regarding the subject being covered in that particular topic. At the end of each module, we will have a capstone (form-based test asking questions about the topics covered in the respective module) which the user can access whenever needed.

As examples of our independent learning modules we can cite Modules I, II and III and their respective topics. Module I (Biodiversity Taxonomy Basis) includes introductory topics (e.g., Topic I — Why do we classify living things; Topic II — Linnaean binomial; Topic III — How is taxonomic information displayed in the literature) aimed at those who don't have a biology/taxonomy background. Module II (The Plazi way) topics (Topic I — Plazi mission; Topic II — Taxomic treatments; Topic III — FAIR taxonomic treatments) are designed in a way that course takers can learn about Plazi processes. Module III (The Golden Gate Imagine) includes topics (Topic I — Introduction to GGI; Topic II — Other User Interface-based alternatives to annotate documents) about the document editor for marking up documents in XML. Other modules include subjects such as individual extractions, material and treatment citations, data quality control, and others.

On completion of a module, the user will be awarded a certificate. The combination of these certificates will grant badges that will translate into server permissions that will allow the user to upload new liberated taxonomic treatments and edit treatments already in the system, for instance. Taxonomic treaments are any piece of information about a given taxon concept that involves, includes, or results from an interpretation of the concept of that given taxon.

Additionally, Plazi TreatmentBank APIs (Application Programming Interface) are currently being expanded and redesigned and the documentation for these long-waited endpoints will be displayed, for the first time, in this talk.

Keywords

API, helpdesk, project management, community involvement, learning resources, data liberation

Presenting author

Carolina Sokolowicz

Presented at

TDWG 2021

Funding program

The BiCIKL (Biodiversity Community Integrated Knowledge Library) project receives funding from the European Union's Horizon 2020 Research and Innovation Action under grant agreement No 101007492

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