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The Jadex GPMN (goal oriented process modeling notation) kernel provides a goal-oriented workflow kernel. The idea is that a workflow is specified as declarative goal hierarchy, which describes what has to be achieved to fulfill the workflow. At runtime goals are pursued by executing plans represented by standard BPMN workflows. The execution of goal-based workflows is achieved by conversion to BDI agents.

The Limbus System is a small light-weight CDI framework managing the Limbus Core Components. The object graph is represented by an XML configuration file or can be build using the Limbus System API. This module delivers an optional system component that visualizes the object graph and its dependencies after initializing: com.remondis.limbus.system.visualize.LimbusSystemVisualizer This component can be added to the Limbus System. To keep the dependencies of this module transparent and light-weight, the graph renderer is declared as an optional dependency. Add the following dependencies to your project to use the visualisation component: <!-- Graph Stream for Visualization feature This is an optional dependency and only required if using the com.remondis.limbus.system.visualize.LimbusSystemVisualizer --> <dependency> <groupId>org.graphstream</groupId> <artifactId>gs-core</artifactId> <version>1.3</version> </dependency> <dependency> <groupId>org.graphstream</groupId> <artifactId>gs-ui</artifactId> <version>1.3</version> </dependency>

Reco4j is an open source project aims at developing a recommendation framework based on graph data sources. We choose graph databases for several reasons. They are NoSQL databases, so "schemaless". This means that it is possible to extend the basic data structure with intermediate information, i.e. similarity value between item and so on. Moreover, since every information is expressed with properties, nodes and relations, the recommendation process can be customized to work on every graph. Reco4j can be used on every graph where "user" and "item" is represented by node and the preferences are modelled as relationship between them. Current implementation leverage on Neo4j as first graph database integrated in our framework.

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.