Page:From documents to datasets - A MediaWiki-based method of annotating and extracting species observations in century-old field notebooks.pdf/3

Rh scribed set of field notebooks, penned by University of Colorado Museum of Natural History founder Junius Henderson (http://en.wikisource.org/wiki/Field_Notes_of_Junius_Henderson). We provide a pragmatic approach for utilizing free, relatively easy-to-use technologies to annotate these notes, and discuss some of the remaining gaps in our toolkits and cyberinfrastructure. We also present a workflow for extracting occurrence records from field notebooks that requires minimal resources (beyond the authors’ time), fosters community involvement, and abstracts the necessary information while maintaining links to its original text, thereby preserving the context that only “first-person precision” can provide. The primary challenges we address are how to: 1) publish these field notes in a way that supports annotation of species occurrence records; 2) extract these records efficiently; 3) convert these records to the most interoperable format; and, 4) store these records and maintain their link to the original field notes.

Background

Remsen et al. (2012) identified conversion of unstructured text into structured data as a key challenge in biodiversity informatics, and showed a working methodology for creating a Darwin Core archive from a conventional floristic checklist. We follow the path laid by those authors, but focus on mining observations from field notebooks. Field notebooks are often “hidden” in archives of institutions, and unlike formally published sources, typically lack a centralized access point (Sheffield et al. 2011), a standardized mark-up language, and any sort of reliable or scalable method of mining content from the notes. Sheffield and Nakasone (2011) from the Smithsonian’s Field Book Project present an excellent high-level view of how existing metadata standards could be used to semantically link collections and field notes. This collections-level schema, however, does not address the need to annotate and extract data from documents. Furthermore, though work has been done linking digital collections to Wikipedia articles (e.g., Lally and Dunford 2007), and though the National Archives have recently partnered with Wikisource to upload their materials for transcription (http://transcribe.archives.gov/), neither of these projects have attempted to annotate or extract data from the materials.

In light of this lack of prior work, and given the observational nature of the notes, we decided that these observations would be best published as Darwin Core records. Though there are other standards used in the digital humanities to mark up scholarly texts (e.g. the Text Encoding Initiative’s standard, http://www.tei-c.org/), none of these are tailored for the encoding of biodiversity data. Darwin Core, on the other hand, is a commonly used metadata schema for describing and exchanging a range of biodiversity data, from museum specimen records to field observations (Wieczorek et al. 2012). In particular, the Global Biodiversity Information Facility (GBIF) uses it for storage, transfer and presentation of biodiversity data.