An Introduction to KeyLines and Network Visualization

Transcription

1 An Introduction to KeyLines and Network Visualization 1. What is KeyLines? Benefits of network visualization Benefits of KeyLines KeyLines architecture Uses of network visualization Where does the data come from? Features of KeyLines... 5 Expand on demand... 6 Combine and group nodes... 6 Array selection ( shapes )... 6 Social network analysis (SNA)... 6 Customizable appearance... 7 Intuitive navigation... 8 Foreign language support... 9 Save, load and PNG export... 9 Find out more... 9 Who should read this white paper? This white paper is aimed at: Potential users of KeyLines Project managers and non-technical staff investigating KeyLines Developers and technical staff seeking a non- technical introduction to KeyLines If you require more detailed information we recommend contacting us to discuss your requirements.

2 1. What is KeyLines? KeyLines is a toolkit used by developers to build sophisticated and powerful network visualization applications. These applications run completely in a web browser and can therefore be easily integrated into existing systems and dashboards, or as standalone applications. Developers can customize the visual appearance of KeyLines, as well as more fundamental elements like the user interface, user interaction and the end-user s feature set. KeyLines is built in the JavaScript programming language, which is most popularly used to run client-side scripts. This makes it lightweight yet powerful capable of visualizing over 1000 elements at once. 2. Benefits of network visualization Network visualization is the practice of visually representing networks of connected entities in a schematic form: Visualizing networks allows you to focus on the connections in data, as much as the entities themselves, which brings an additional dimension to data analysis. In particular, network visualization is effective for finding patterns in complex connected datasets. Compared to alternative techniques, e.g. data- mining or rule scoring, network visualization is: Faster by visualizing large volumes of data at once, decision making becomes faster and more efficient allowing you to take the required action sooner. More accurate make the right decisions and avoid costly mistakes with sophisticated visualization tools that combine machine power with the unrivalled human ability to recognize patterns. Deeper ensure decisions are taken with a 360-degree view by visualizing data within its connected environment. More understandable convince colleagues and get a shared view of a situation with accessible, visual evidence. Organizations harnessing network visualization capabilities usually benefit from: Faster, more cost-effective decision-making More efficient trend identification Improved processes and data management More rounded data analysis compared with using a single approach - 2 -

3 3. Uses of network visualization Network visualization can be applied to any connected dataset, but has found particular value in several key environments: Fraud management visualizing frauds and fraud networks to detect suspicious behavior and identify trends. Law enforcement mapping connections between crimes and criminals to understand emerging crime patterns and solve complex cases. Counter terrorism detecting cell structure, highlighting weaknesses and chains of command. IT and Telecommunications mapping hardware networks and dependencies and visualizing connections between users. Sales and Marketing finding decision makers, thought leaders and understanding customer social influence. Social Networks see the movement of news and information around highly connected networks of people. Logistics mapping physical networks, for example oil and gas pipelines or transport networks. 4. Benefits of KeyLines The widest reach a visualization application is most valuable when it is easily and readily accessible. Being browser based, KeyLines will work on any device without any software installation. This removes the barriers that stop visualization applications being used to generate high quality insight. Highly flexible KeyLines will work with any database, any server almost any browser. This flexible architecture means it can be deployed in complex environments and alongside legacy IT systems without expensive integration projects. The fastest option Building a custom network visualization application from scratch is time consuming and requires a lot of expensive development resource. Using the KeyLines toolkit eliminates these problems and saves thousands of dollars over building a component from scratch without compromising on specifications. Proven technology unreliable and unproven software frustrates users, wastes time and wastes money. KeyLines has been successfully deployed in high profile and complex organizations the largest deployments have tens of thousands of users and has a dedicated support team on hand to fix bugs if they occur. Eye-catching hundreds of hours have been invested in making KeyLines expressive, interactive and good-looking. This means the applications built with the toolkit are professional and stand out from the crowd. Built by experts Cambridge Intelligence, the company that builds KeyLines, has over 40 years experience of building network visualization software. Combining this visualization knowledge with the customer s expert subject knowledge results in applications that are a joy to use. 5. KeyLines architecture KeyLines consists of a JavaScript and Flash file that are deployed to a web server and embedded into a webpage. As the end-user interacts with KeyLines in the webpage, events (such as clicking or dragging) are - 3 -

4 raised. These can be customized to build a full user experience - for example, right-click could generate a menu. When these events occur, the JavaScript Controller communicates back to the data store, if required, and calls a set of functions, such as automatic layouts or expand. These functions and events are communicated to the KeyLines component, which renders the required graphics in the browser using either the HTML5 Canvas element or a Flash fallback. Key benefits of the KeyLines architecture include Flexibility KeyLines fits most corporate IT systems. Compatibility with all major browsers, including IE7. Lightweight graphic rendering occurs client side, removing the requirement for dedicated visualization servers and increased bandwidth. Security all data remains inside the corporate firewall The KeyLines architecture 6. Where does the data come from? KeyLines is database agnostic. Data can come from any source as long as it can be put into an entity- link structure. This is then parsed into KeyLines published JSON format. Graph databases are a particularly popular type of database for network visualization as they store data in a graph structure, including nodes, edges (links) and properties. KeyLines provides easy integration with all graph databases, including: Infinitegraph, by Objectivity, is a high- performance, scalable graph database that can connect to KeyLines via a Restlet Server Neo4J, by Neo Technologies, is the world s most popular graph database and links to KeyLines using the Cypher query language Titan, by Aurelius, is an open source graph database capable of linking to KeyLines via a technology known as Rexter. Other data store options include: - 4 -

5 Standard SQL databases - relational databases that uses the SQL programming language, including MySQL and SQLite. Non-SQL databases - non-relational databases that offer more efficient data lookup, including the graph databases listed above and MongoDB, Unstructured data. 7. Features of KeyLines KeyLines comes equipped with a complete range of sophisticated features. These can be easily written into your deployment using code detailed in our SDK site. Precise Automatic Layouts Automatic layouts can be applied to data to untangle nodes and links in a consistent, precise and visually clear way. Layouts include: Standard rearranges elements to reduce overlap and distribute elements evenly around the chart. Structural groups nodes of similar properties into fans around a central node or cluster. Radial arranges child nodes in concentric circles around the parent, with generations grouped in new orbits. Hierarchical child nodes are shown in horizontal layers below their parents. Incremental minimizes overlap as new chart elements are added. As the dataset increases, new items are automatically placed in optimal locations. Standard layout Structural layout Radial layout Hierarchical layout - 5 -

6 Expand on demand! Once a data connection is established, additional data can be added to charts on-demand using an expand function. This enables the client to fetch related data from the data source. The incremental layout automatically optimizes data loading by positioning new items as they are added. Combine and group nodes Simplify complex networks by combining nodes into single entities, or grouping multiple nodes and links into groups that can be ungrouped on demand. This feature can also be used to reflect changing dynamics (e.g. if a group of individuals form a gang) or to temporarily correct erroneous data (e.g. duplicates or aliases). Background nodes A background layer can be created to alpha-blend, or ghost, less important chart elements. This is useful for focusing attention on a certain group of nodes whilst maintaining an overview of the entire network. Array selection ( shapes ) Select an array of nodes using a shape tool. These nodes can then be manipulated independently or detached from the surrounding network. Social network analysis (SNA) KeyLines SNA measures offer advanced insight into the relationships between entities and the flow of information amongst them. The measures currently available in KeyLines are: Degree (top image) identifies entities with the most links to other entities. Degree centrality can be calculated based on only inbound links, only outbound links, or both. Nodes with high outbound degree often generate a lot of content; those with a high inbound degree consume a lot of content. Betweenness (second image) identifies entities that most frequently act as bridges between other entities. When doing this, KeyLines can take link direction and link weights into account. A high betweenness score often indicates someone is a gatekeeper of information in a network, or has access to data from the most disparate parts of the network

7 Closeness (third image) identifies entities with the best access to the rest of the network. KeyLines does this by calculating the maximum link distance from each node to reach all other nodes on the chart. The node that can reach the entire network in the shortest number of links has the highest closeness score. This usually indicates the most important node in the network. Distance measures the distance from one node to another, either by counting the number of hops, or by calculating the combined weight of the links traversed. Shortest path (fourth image) calculate the shortest route between two entities, with directed and weighted variants. Visualize networks through time Network data is rarely static. Networks evolve and reshape over time, with new connections and communities forming and dissolving constantly. The analysts who study this data need to be able to comprehensively understand how these dynamic networks are behaving before making judgments or taking decisions. The KeyLines time bar component has been designed specifically to overcome this challenge, offering an intuitive way to rapidly understand how networks behave through time. The KeyLines time bar is made up of several visual elements that integrate fully with the main KeyLines Network Visualization chart. When a user interacts with the time bar e.g. by reducing the scope from a full week to a single day, the KeyLines chart instantly updates to reflect the changed parameters. Alternatively, the time bar can be deployed as a standalone component for understanding how volumes change through time

8 Customizable appearance Every element of a KeyLines chart can be customized to suit the dataset or product branding. Chart elements that can be adapted include: Nodes: color, size, shape, animation, use of image or symbol, use of border, use of glyphs, use of label Node border: color, weight Node label: font color, font size, font weight, background color Links: color, weight, outline, direction, curve, use of label Link label: font color, font size, font weight, background color Glyphs: color, size, position on node, position on glyph, animation, use of image or symbol, label (up to 4 characters) Background: color, use of image / watermark, use of logo Customizable events! KeyLines event model allows considerable flexibility when building an intuitive user experience.!as the enduser interacts with KeyLines, events are raised and bound to actions. For example, a right-click interactionevent could raise an event to display a menu of options in KeyLines. The KeyLines SDK currently supports 20 different events.! Intuitive navigation! A Google Maps-style set of controls offer users an intuitive way to navigate their charts, including zoom, pan, highlight, grab and a chart overview.

9 Foreign language support! The HTML5 Canvas version of KeyLines can support text in many foreign languages.! Save, load and PNG export! Working charts can be saved, shared and re-loaded. This allows teams to work with a central collection of charts, for intelligence to be shared and for particularly useful charts to be saved and re-accessed at a later date. Charts can also be exported as high-resolution PNG images with the click of a button, for sharing or reporting. Find out more For more information, or to get an evaluation license for KeyLines, please get in touch: UK: +44 (0) US: +1 (775)

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