Data Interpretation

Moksha provides various mechanisms that allow applications to more easily interpret dynamic data and act on it.

Collaborative glue

Although it does not yet, Moksha will allow anything to be tagged, shared, discussed, annotated, rated, etc.

Live streams

Any data source, even if moksha has to occasionally poll it, can be displayed as a ‘live’ widget. Producers can also easily expose themselves through an AMQP/STOMP message queue or 0mq message filter, allowing other applications and services to interact with new data, as it is discovered.

Consumers

Moksha allows plugins to monitor arbitrary message “topics”, giving developers the ability to register actions on arbitrary events.

Extension Points

Moksha gives developers the ability to add additional functionality to predictable patterns found within dynamic data streams. For example, an extension point could find all occurences of known project names within a data feed, and easily turn them into a dynamic hover menu that could display related data.

Table Of Contents

Previous topic

Data Aggregation

Next topic

Data Persistence

This Page