A wide variety of information or 'metadata' is required when undertaking dendrochronological sampling. Traditionally, researchers record observations and measurements on field notebooks and/or paper recording forms, and use digital cameras and hand-held GPS devices to capture images and record locations. In the lab, field notes are often manually entered into spreadsheets or personal databases, which are then sometimes linked to images and GPS waypoints. This process is both time consuming and prone to human and instrument error. Specialised hardware technology exists to marry these data sources, but costs can be prohibitive for small scale operations (>$2000 USD). Such systems often include proprietary software that is tailored to very specific needs and might require a high level of expertise to use. We report on the successful testing and deployment of a dendrochronological field data collection system utilising affordable off-the-shelf devices ($100-300 USD). The method builds upon established open source software that has been widely used in developing countries for public health projects as well as to assist in disaster recovery operations. It includes customisable forms for digital data entry in the field, and a marrying of accurate GPS location with geotagged photographs (with possible extensions to other measuring devices via Bluetooth) into structured data fields that are easy to learn and operate. Digital data collection is less prone to human error and efficiently captures a range of important metadata. In our experience, the hardware proved field worthy in terms of size, ruggedness, and dependability (e.g., battery life). The system integrates directly with the Tellervo software to both create forms and populate the database, providing end users with the ability to tailor the solution to their particular field data collection needs.

There are at least 21 dendro-data formats used in dendrochronology laboratories around the world. Many of these formats are read by a limited number of programs, thereby inhibiting collaboration, limiting critical review of analyses, and risking the long-term accessibility of datasets. Some of the older formats are supported by a single program and are falling into disuse, opening the risk for data to become obsolete and unreadable. These formats also have a variety of flaws, including but not limited to no accurate method for denoting measuring units, little or no metadata support, lack of support for variables other than whole ring widths (e.g. earlywood/latewood widths, ratios and density). The proposed long-term solution is the adoption of a universal data standard such as the Tree-Ring Data Standard (TRiDaS). In the short and medium term, however, a tool is required that is capable of converting not only back and forth to this standard, but between any of the existing formats in use today. Such a tool is also required to provide continued access to data archived in obscure formats. This paper describes TRiCYCLE, a new application that does just this. TRiCYCLE is an open-source, cross-platform, desktop application for the conversion of the most commonly used data formats. Two open source Java libraries upon which TRiCYCLE depends are also described. These libraries can be used by developers to implement support for all data formats within their own applications.