A flexible and extendable library for data exploration, data analytics, data authoring and knowledge sharing.
Tap into all of your data
Connect multiple private or public data sources & browse one cumulative knowledge graph
Through the metaphactory platform, Sputniq supports the most prominent graph databases, including Stardog, blazegraph, Amazon Neptune, etc. » Full list
Interact smoothly with data
Upload unfamiliar data or ontologies and start exploring right away
Interactively build diagrams and perform deep-dive analyses
Drag'n'drop data bits into diagrams
Visual data and ontology authoring
Turn data into knowledge
Ask better questions and get precise, contextually-rich answers
Share knowledge with collaborators
Make better business decisions by highlighting patterns and showing relations
HOW DOES IT WORK?
Sputniq is tightly integrated into metaphactory's search and exploration framework and is being delivered to metaphacts customers as part of metaphactory.
Sputniq is seamlessly coupled with metaphactory and has truly become an integral platform component. Just as any other metaphactory platform component, it can be configured and applied to platform templates. This is enabled by its rich API and highly flexible visual templating mechanism for vertexes and edges.
Diagrams are managed as native assets, which means that users can save and open them anytime.
One of the main advantages of the Sputniq integration into metaphactory is that this data browser can be used out-of-the-box, i.e., on any dataset and with no prior configuration.
End-users easily navigate through large data sets, become aware of the data structure, data volume and the relevant knowledge they conceal, and quickly find answers to their questions. This is achieved through Sputniq's support for:
queries over several data sources and navigation across multiple datasets,
incremental exploration (i.e., expanding nodes to see connected entities in the knowledge graph),
answering the question of "how many" by counting the number of connected entities, classes, individuals in classes, etc.,
search across all types of data: classes, individuals, connections, etc.
Sputniq's ability to hide the underlying data complexity and engage users with visual interaction enables various real-life analysis scenarios, specifically:
visualize data in various formats and gain insights into meaningful facts,
perform drill-down analyses,
find paths between entities and match patterns,
perform "what-if" analyses,
group similar concepts into group-nodes for easier perception and quantitative analysis,
define visual templates for types of nodes and connections,
support for "property graph" model and "collapsible paths" that simplify the representation of knowledge,
share findings with colleagues.
Visual Data Authoring
End-users can augment the knowledge graph and its ontologies by leveraging Sputniq's most recent features for visual knowledge graph authoring, specifically:
adding entities to and removing them from the dataset,
modifying properties of entities,
adding or removing connections between entities,
customizing nodes to embed rich content, e.g., embedded videos,
authoring basic ontologies,
on-the-fly validation of changes against the ontology constrains.
Data Model Documentation and Knowledge Distribution
With Sputniq, end-users can easily document data and ontologies by creating diagrams around it, and share their knowledge base with colleagues. To this end, Sputniq allows for:
creating diagrams and posting them as illustrations,
automatically producing example diagrams from the published RDF,
embedding diagrams into documentation pages,
configuring how diagrams are displayed to readers (e.g., read-only).
Highly customizable look and feel
Large graphs supported while adding unprecedented interactivity
Multiple data sources navigated seamlessly in one graph
Visual data & ontology authoring
Finding paths between two objects
LEARN MORE ABOUT SPUTNIQ
Try the demo system below and experience Sputniq first-hand!