Refine
Document Type
- Article (1)
- Conference Proceeding (1)
Language
- English (2)
Has Fulltext
- yes (2) (remove)
Is part of the Bibliography
- no (2)
Keywords
- Annotation (1)
- BIOfid (1)
- Biodiversity (1)
- Inter-annotator agreement (1)
- Named entity recognition (1)
- Semantic portal (1)
- Specialized information service (1)
- Taxon (1)
Institute
Biodiversity information is contained in countless digitized and unprocessed scholarly texts. Although automated extraction of these data has been gaining momentum for years, there are still innumerable text sources that are poorly accessible and require a more advanced range of methods to extract relevant information. To improve the access to semantic biodiversity information, we have launched the BIOfid project (www.biofid.de) and have developed a portal to access the semantics of German language biodiversity texts, mainly from the 19th and 20th century. However, to make such a portal work, a couple of methods had to be developed or adapted first. In particular, text-technological information extraction methods were needed, which extract the required information from the texts. Such methods draw on machine learning techniques, which in turn are trained by learning data. To this end, among others, we gathered the BIOfid text corpus, which is a cooperatively built resource, developed by biologists, text technologists, and linguists. A special feature of BIOfid is its multiple annotation approach, which takes into account both general and biology-specific classifications, and by this means goes beyond previous, typically taxon- or ontology-driven proper name detection. We describe the design decisions and the genuine Annotation Hub Framework underlying the BIOfid annotations and present agreement results. The tools used to create the annotations are introduced, and the use of the data in the semantic portal is described. Finally, some general lessons, in particular with multiple annotation projects, are drawn.
In an ideal world, extraction of machine-readable data and knowledge from natural-language biodiversity literature would be done automatically, but not so currently. The BIOfid project has developed some tools that can help with important parts of this highly demanding task, while certain parts of the workflow cannot be automated yet. BIOfid focuses on the 20th century legacy literature, a large part of which is only available in printed form. In this workshop, we will present the current state of the art in mobilisation of data from our corpus, as well as some challenges ahead of us. Together with the participants, we will exercise or explain the following tasks (some of which can be performed by the participants themselves, while other tasks currently require execution by our specialists with special equipment): Preparation of text files as an input; pre-processing with TextImager/TextAnnotator; semiautomated annotation and linking of named entities; generation of output in various formats; evaluation of the output. The workshop will also provide an outlook for further developments regarding extraction of statements from natural-language literature, with the long-term aim to produce machine-readable data from literature that can extend biodiversity databases and knowledge graphs.