Time series of zooplankton abundance at station L4 in the English Channel from 1988 to 2011

Ongoing zooplankton research at the Plymouth Marine Laboratory has established a time series of zooplankton species since 1988 at L4, a coastal station off Plymouth. Samples were collected by vertical net hauls (WP2 net, mesh 200 µm; UNESCO 1968) from the sea floor (approximately 50 m) to the surface and stored in 4% formalin. Much of the zooplankton analysis has been to the level of "major taxonomic groups" only, and a number of different analysts have participated over the years. The level of expertise has generally been consistent, but the user should be aware that levels of taxonomic discrimination may vary during the course of the dataset. The dominant calanoid copepods are generally well discriminated to species throughout. Calanus has not been routinely examined for species determination, the assumption being that the local population is entirely composed of Calanus helgolandicus. In certain years there has been a particular interest in Temora stylifera, Centropages cherchiae and other species reflected in the dataset. The lack of records in other previous years does not necessarily reflect species absence. We view it as essential for all users of L4 plankton data to establish and maintain contact with the nominated current data originators as well as fully consulting the metadata. While not impinging on free data access, this ensures that this large, species-rich but slightly complex species database is being used in the correct way, and any potential issues with the data are clarified. Furthermore, a proper dialogue with these local experts on the time series will enable where appropriate the most recent sampling timepoints to be used. The data can be downloaded from BODC or from doi:10.1594/PANGAEA.778092 as files for each year by searching for "L4 zooplankton". The most comprehensive dataset is the version downloadable directly from this page. The entire set of zooplankton samples is stored at the Plymouth Marine Laboratory in buffered formalin, and may be available for further taxonomic analysis on request.

Reference list of 120 datasets from time series station Payerne used for exploratory search

The analysis of time-dependent data is an important problem in many application domains, and interactive visualization of time-series data can help in understanding patterns in large time series data. Many effective approaches already exist for visual analysis of univariate time series supporting tasks such as assessment of data quality, detection of outliers, or identification of periodically or frequently occurring patterns. However, much fewer approaches exist which support multivariate time series. The existence of multiple values per time stamp makes the analysis task per se harder, and existing visualization techniques often do not scale well. We introduce an approach for visual analysis of large multivariate time-dependent data, based on the idea of projecting multivariate measurements to a 2D display, visualizing the time dimension by trajectories. We use visual data aggregation metaphors based on grouping of similar data elements to scale with multivariate time series. Aggregation procedures can either be based on statistical properties of the data or on data clustering routines. Appropriately defined user controls allow to navigate and explore the data and interactively steer the parameters of the data aggregation to enhance data analysis. We present an implementation of our approach and apply it on a comprehensive data set from the field of earth bservation, demonstrating the applicability and usefulness of our approach.