MARS: A multi-level array representation for simulation data

TL;DR: A new type of query, subarray skyline, is proposed that provides a way to find meaningful subarrays or filter less meaningful sub arrays considering attributes and an efficient processing method, ReSKY, is introduced for sub array skyline query processing.

TL;DR: In this paper , a compression scheme, SEACOW, is proposed for storing and querying multidimensional array data, which is specially designed to be efficient for both dimension-based and value-based exploration.

TL;DR: Analyzing verbal data from think-aloud protocols, it is found that increased latency reduces the rate at which users make observations, draw generalizations and generate hypotheses, causing users to shift exploration strategy, in turn affecting performance.

TL;DR: RasDaMan is a universal — i.e., domain-independent — array DBMS for multidimensional arrays of arbitrary size and structure that offers flexible retrieval and manipulation and efficient server-based query evaluation.

TL;DR: This paper presents ForeCache, a general-purpose tool for exploratory browsing of large datasets, which utilizes a client-server architecture, where the user interacts with a lightweight client-side interface to browse datasets, and the data to be browsed is retrieved from a DBMS running on a back-end server.

TL;DR: This paper describes a method for the Hilbert Curve for indexing multi-dimensional data using the Z-Order Curve since it has superior clustering properties.