Reference list of 265 sources used for the discovery of relationships between data clusters and metadata properties

Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.

Reference list of 269 sources used for exploratory search

Today's digital libraries (DLs) archive vast amounts of information in the form of text, videos, images, data measurements, etc. User access to DL content can rely on similarity between metadata elements, or similarity between the data itself (content-based similarity). We consider the problem of exploratory search in large DLs of time-oriented data. We propose a novel approach for overview-first exploration of data collections based on user-selected metadata properties. In a 2D layout representing entities of the selected property are laid out based on their similarity with respect to the underlying data content. The display is enhanced by compact summarizations of underlying data elements, and forms the basis for exploratory navigation of users in the data space. The approach is proposed as an interface for visual exploration, leading the user to discover interesting relationships between data items relying on content-based similarity between data items and their respective metadata labels. We apply the method on real data sets from the earth observation community, showing its applicability and usefulness.

Compilation of 220 sediment core d13C data from the glacial Atlantic Ocean

We compare a compilation of 220 sediment core d13C data from the glacial Atlantic Ocean with three-dimensional ocean circulation simulations including a marine carbon cycle model. The carbon cycle model employs circulation fields which were derived from previous climate simulations. All sediment data have been thoroughly quality controlled, focusing on epibenthic foraminiferal species (such as Cibicidoides wuellerstorfi or Planulina ariminensis) to improve the comparability of model and sediment core carbon isotopes. The model captures the general d13C pattern indicated by present-day water column data and Late Holocene sediment cores but underestimates intermediate and deep water values in the South Atlantic. The best agreement with glacial reconstructions is obtained for a model scenario with an altered freshwater balance in the Southern Ocean that mimics enhanced northward sea ice export and melting away from the zone of sea ice production. This results in a shoaled and weakened North Atlantic Deep Water flow and intensified Antarctic Bottom Water export, hence confirming previous reconstructions from paleoproxy records. Moreover, the modeled abyssal ocean is very cold and very saline, which is in line with other proxy data evidence.

Location and ages of terrestrial peatlands located on continental shelves and in coastal sediments

This synthesis dataset contains records of freshwater peat and lake sediments from continental shelves and coastal areas. Information included is site location (when available), thickness and description of terrestrial sediments as well as underlying and overlying sediments, dates (when available), and references.