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In such studies the diversity of objects and total numbers of objects available for study are both very high. The need to count many objects in many categories is particularly acute in biodiversity related disciplines, for example, field surveys of species diversity, or species counts of fossil assemblages in micropaleontology. None of these, however, are well suited to counting larger numbers of categories, which is common in ecology, and in related fields such as paleontology.

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Numerous inexpensive or free simple tally counter programs are available that can replace mechanical counter buttons, for example, dozens of simple smartphone/tablet apps, or more sophisticated desktop apps, for example, Versacount: ( Kim & DeRisi, 2010) ( Table 1). There are many reasons for this including cost, inflexibility, compatibility and inadequate ease of use.

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Computer ‘point-counting’ programs can in principle replace these methods and at the same time provide additional functions that mechanical methods cannot, such as continuous statistical summaries of the data as it is being collected, which provides useful feedback to the observer on how complete or accurate the dataset being collected is.ĭespite these obvious advantages, counting programs have yet to fully replace manual methods. Both methods are slow and require re-entering the count values into a computer afterwards before analysis, adding additional time and possibilities for error.

Up until the widespread use of desktop computers, such counts were done mostly either with the aid of mechanical counters (including arrays of several buttons, to allow counting of multiple categories) or tallied by hand on printed list forms. This is particularly common in ecology, organismal biology and behavioural sciences, where numeric data on the frequencies of occurrences of biologic phenomena are desired, but the objects or phenomena to be counted are too complex to identify by instruments or fully computerized image analysis systems. Quantitative data about many aspects of the natural world are collected in modern science with the use of instruments, but a substantial amount of observational data is still collected by human observation. Introduction Human observations as a source of scientific data

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‘Stratigraphic occurrence data’ file format combines extensive sample metadata and a flexible structure for recording occurrence data of species or other categories in a series of samples. Lastly, we describe the file format used by Raritas and propose it as a standard for storing geologic biodiversity data. The program explicitly supports a rare category count mode which makes it easier to collect quantitative data on rare categories, for example, rare species which are important in biodiversity surveys. Raritas is written in Python and can be run as a standalone app for recent versions of either MacOS or Windows, or from the command line as easily customized source code. We describe a new open-source program for this purpose-Raritas.

Existing computer counting programs used to record such data have various limitations, including inflexibility and cost. PeerJ 6: e5453 Īcquiring data on the occurrences of many types of difficult to identify objects are often still made by human observation, for example, in biodiversity and paleontologic research. Raritas: a program for counting high diversity categorical data with highly unequal abundances. Cite this article Lazarus DB, Renaudie J, Lenz D, Diver P, Klump J. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. Licence This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. 4 CSIRO, Mineral Resources, Kensington, NSW, Australia DOI 10.7717/peerj.5453 Published Accepted Received Academic Editor Donald Baird Subject Areas Biodiversity, Bioinformatics, Ecology, Paleontology Keywords Software, Point-counting, Rarity, Data standards, Micropaleontology, Biostratigraphy, Biodiversity, Ecology, Python, Range chart Copyright © 2018 Lazarus et al.