On Generating SHACL Shapes from Collective Collection of Plant Trait Data

Dadan Ridwan Saleh, Yulia Aris Kartika, Zaenal Akbar, Adila Alfa Krisnadhi, Widya Fatriasari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Collective data collection has become common in various domains, including biodiversity science. Multiple individuals work on the same biological samples or specimens using various scientific tools to measure different characteristics. Moreover, the measurements are typically regulated by different data collection procedures and protocols. Integrating and guaranteeing the quality of the data has become a significant issue. One solution is to adopt the RDF (Resource Description Framework) data model in combination with a language for validating RDF graphs such as SHACL (Shapes Constraint Language). The RDF data model provides flexibility in accommodating multiple data schemas, while SHACL uses a set of conditions so called shapes, to validate the RDF data graphs. The remaining challenge is an effective method to define SHACL shapes that can be used to validate any given RDF data. This work introduces a semi-Automatic database-driven solution to generate SHACL shapes. The solution relies on the database's internal structure and data items' values. The solution was applied to a traits database from natural fiber plants in Indonesia, where a high number of individual shapes were successfully generated. Furthermore, a qualitative evaluation indicated the appropriate quality of the shapes. This work contributes to increasing the quality of biodiversity data collections, which has become an essential factor in Big Biodiversity Data processing.

Original languageEnglish
Title of host publicationProceeding - 2022 9th International Conference on Computer, Control, Informatics and Its Applications
Subtitle of host publicationDigital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022
PublisherAssociation for Computing Machinery
Pages326-330
Number of pages5
ISBN (Electronic)9781450397919
DOIs
Publication statusPublished - 22 Nov 2022
Event9th International Conference on Computer, Control, Informatics and Its Applications: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022 - Virtual, Online, Indonesia
Duration: 22 Nov 202223 Nov 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference9th International Conference on Computer, Control, Informatics and Its Applications: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period22/11/2223/11/22

Keywords

  • biodiversity
  • collective data
  • plant trait data
  • SHACL

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