Academic Program: Free Graph and Data Visualization Software for Education

Proof of enrollment

Participants must be currently enrolled as full-time or part-time students or faculty at an accredited university or college. Proof of active enrollment or employment may be required.

Valid school email address

Registration must be completed using a valid school-issued email address (e.g., .edu or institution domain) to confirm eligibility.

Download and install

That's all there is to it! Request an evaluation and once submitted, your request will be reviewed within 2 business days. If approved, you receive an email with the download and installation instructions.

Graph-based solutions help students explore how structural properties like ring formation, branching, and connectivity determine a molecule's reactivity, and lets professors map multi-step reaction networks as directed graphs from reactants to products.

Trade relationships between nations, firms in a supply chain, or agents in a market can all be represented as nodes connected by directed edges representing flows of goods, capital, dependency, or influence. Graph analysis reveals which nodes are most critical, and most vulnerable to disruption.

Graph theory is a discipline unto itself, where students study the properties of nodes and edges directly: connectivity, paths, planarity, coloring, and traversal. A graph visualization and analysis platform helps them construct and manipulate these structures rather than just reason about them abstractly.

Protein interaction networks map biological molecules as nodes with edges representing physical binding, a key aspect in drug discovery for identifying intervention targets. Disease transmission maps patients and pathogens as nodes, with edges representing exposure or contact.

Social network analysis, mapping centrality, identifying brokers between clusters, or detecting echo chambers, is a primary research method, not just a visualization aid.

Cybersecurity benefits by graphing network vulnerabilities and attack paths, helping identify critical nodes before threats propagate. In cryptography, graph properties like adjacency matrices and connectivity enable innovative encryption schemes resistant to classical attacks.

Complex engineered systems such as aircraft, power grids, and software platforms are modeled as graphs where subsystems are nodes and dependencies or data flows are edges. Analyzing that graph reveals single points of failure (high-centrality nodes with no redundancy), failure cascade paths, and integration bottlenecks that aren't visible from component-level specs alone.

Gene regulatory networks map genes as nodes and activation or inhibition relationships as directed edges, letting researchers see how a single mutation can ripple through an entire biological system. Neural circuits, metabolic pathways, and ecological community structures are all similarly graph-shaped, making node-and-edge analysis central to modern biological research across scales from the cell to the ecosystem.

Stakeholder maps, merger integration planning, and supply chain risk analysis all benefit from modeling entities as nodes and relationships as edges, making visible who actually drives decisions versus who holds the formal title. Businesses run on processes, which are complex maps of shared responsibility.