Download JAR files tagged by exploration with all dependencies

Proof exploration capabilities for key.ui

Plugin module that allows for data set exploration.

FijiRelax : 3D+t MRI analysis and exploration using multi-echo spin-echo sequences

A self-service search and analysis tool enabling interactive exploration of SPARQL endpoints.

APE is a command line tool and an API for the automated exploration of possible computational pipelines (workflows) from large collections of computational tools.

Extensions to netCDF reader for file formats published by Japanese Aerospace Exploration Agency (JAXA).

A library for general purpose exploration through a set of actions. This is most applicable in a reinforcement or bandit setting, althought it is most often tested with Vowpal Wabbit.

A file reader of the sas7bdat file format, aka. SAS tables. Includes adaption for the MetaModel framework to allow more elaborate querying and exploration abilities.

ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extensible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.