Technological developments open up new opportunities for collaboration between biodiversity researchers and the general public. Three exemplary case studies were reviewed from literature: digitizing museum specimens, text-mining archived expedition journals and handling environmental monitoring data. Data management principles were applied to refine the ensuing requirements. Specific requirements were found to exist in three areas: collecting data, sharing data and improving data quality. Implications for data governance and quality control are discussed.
Knowledge of hearing ability, as represented in audiograms, is essential for understanding how animals acoustically perceive their environment, predicting and counteracting the effects of anthropogenic noise, and managing wildlife. Audiogram data and relevant background information are currently only available embedded in the text of individual scientific publications in various unstandardized formats. This heterogeneity makes it hard to access, compare, and integrate audiograms. The Animal Audiogram Database (https://animalaudiograms.org) assembles published audiogram data, metadata about the corresponding experiments, and links to the original publications in a consistent format. The database content is the result of an extensive survey of the scientific literature and manual curation of the audiometric data found therein. As of November 1, 2021, the database contains 306 audiogram datasets from 34 animal species. The scope and format of the provided metadata and design of the database interface were established by active research community involvement. Options to compare audiograms and download datasets in structured formats are provided. With the focus currently on vertebrates and hearing in underwater environments, the database is drafted as a free and open resource for facilitating the review and correction of the contained data and collaborative extension with audiogram data from any taxonomic group and habitat.
Technological developments open up new opportunities for collaboration between biodiversity researchers and the general public. Three exemplary case studies were reviewed from literature: digitizing museum specimens, text-mining archived expedition journals and handling environmental monitoring data. Data management principles were applied to refine the ensuing requirements. Specific requirements were found to exist in three areas: collecting data, sharing data and improving data quality. Implications for data governance and quality control are discussed.
Maintaining a semantic wiki is challenging. Coping with increasingly complex wikis led to the development of a methodical approach for simplifying the creation and maintenance of semantic wikis. The methodical approach used involves modeling the semantic relationships underlying the information in the wiki as an ontology, and then programmatically creating the wiki from the ontology constructs. A methodical approach for creating and maintaining wikis greatly simplifies the creation and maintenance of semantic wikis. Furthermore, reusing vocabularies and taxonomies throughout several projects becomes manageable. The approach was implemented as open source software that maps ontology constructs to the wiki artifacts, and practical applications are discussed.
Technological developments open up new opportunities for collaboration between biodiversity researchers and the general public. Three exemplary case studies were reviewed from literature: digitizing museum specimens, text-mining archived expedition journals and handling environmental monitoring data. Data management principles were applied to refine the ensuing requirements. Specific requirements were found to exist in three areas: collecting data, sharing data and improving data quality. Implications for data governance and quality control are discussed.
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