Advancing access to biodiversity data using the SALIX method and digital field guides

The Arizona State University Herbarium began in 1896 when Professor Fredrick Irish collected the first recorded Arizona specimen for what was then called the Tempe Normal School - a Parkinsonia microphylla. Since then, the collection has grown to approximately 400,000 specimens of vascular plants and lichens. The most recent project includes the digitization - both the imaging and databasing - of approximately 55,000 vascular plant specimens from Latin America. To accomplish this efficiently, possibilities in non-traditional methods, including both new and existing technologies, were explored. SALIX (semi-automatic label information extraction) was developed as the central tool to handle automatic parsing, along with BarcodeRenamer (BCR) to automate image file renaming by barcode. These two developments, combined with existing technologies, make up the SALIX Method. The SALIX Method provides a way to digitize herbarium specimens more efficiently than the traditional approach of entering data solely through keystroking. Using digital imaging, optical character recognition, and automatic parsing, I found that the SALIX Method processes data at an average rate that is 30% faster than typing. Data entry speed is dependent on user proficiency, label quality, and to a lesser degree, label length. This method is used to capture full specimen records, including close-up images where applicable. Access to biodiversity data is limited by the time and resources required to digitize, but I have found that it is possible to do so at a rate that is faster than typing. Finally, I experiment with the use of digital field guides in advancing access to biodiversity data, to stimulate public engagement in natural history collections.