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Background: More and more herbaria are digitising their collections. Images of specimens are made available online to facilitate access to them and allow extraction of information from them. Transcription of the data written on specimens is critical for general discoverability and enables incorporation into large aggregated research datasets. Different methods, such as crowdsourcing and artificial intelligence, are being developed to optimise transcription, but herbarium specimens pose difficulties in data extraction for many reasons., New Information: To provide developers of transcription methods with a means of optimisation, we have compiled a benchmark dataset of 1,800 herbarium specimen images with corresponding transcribed data. These images originate from nine different collections and include specimens that reflect the multiple potential obstacles that transcription methods may encounter, such as differences in language, text format (printed or handwritten), specimen age and nomenclatural type status. We are making these specimens available with a Creative Commons Zero licence waiver and with permanent online storage of the data. By doing this, we are minimising the obstacles to the use of these images for transcription training. This benchmark dataset of images may also be used where a defined and documented set of herbarium specimens is needed, such as for the extraction of morphological traits, handwriting recognition and colour analysis of specimens.

Background: Online systems for observation reporting by citizen scientists have been operating for many years. iNaturalist (California Academy of Sciences 2016), eBird (Cornell Lab of Ornithology 2016) and Observado (Observation International 2016) are well-known international systems, Artportalen (Swedish Species Information Centre 2016) and Artsobservasjoner (Norwegian Biodiversity Information Centre 2016) are Scandinavian. In addition, databases and online solutions exist that are more directly research-oriented but still offer participation by citizen scientists, such as the PlutoF (University of Tartu Natural History Museum 2016) platform. The University of Tartu Natural History Museum maintains the PlutoF platform (Abarenkov et al. 2010) for storing and managing biodiversity data, including taxon observations. In 2014, development was started to integrate an observation app "Minu loodusheli"/"My naturesound" (University of Tartu Natural History Museum 2017b) (My naturesound, Fig. 1) within PlutoF system. In 2017, an English language version of the app (University of Tartu Natural History Museum 2017c) was launched that includes nearly all major sound-producing taxon groups in its taxonomy. The application also acts as a practical tool for collecting and publishing occurrence data for the Global Biodiversity Information Facility (Global Biodiversity Information Facility 2017) in standardized Darwin Core format together with download links to the multimedia files. Although the sound recording ability of mobile phones opens new opportunities to validate taxon occurrences, current technological solutions limit the use of recordings in biodiversity research.The "My naturesound" allows the user to record taxon occurrences and to provide audio recordings as evidence. After installing the application, the user is promted to login with PlutoF system credentials or to register with PlutoF. The application is targeted primarely to citizen scientists, but researchers themselves can also use it as a tool for easy annotation of taxon occurrences., New Information: The dataset consists observation data of birds, amphibians and insects by citizen scientists with on site audio recordings. The dataset gives the possibility to analyze the suitablility of mobile devices for recording animal vocalizations and their use in reporting.