Network Workbench ( Weixia (Bonnie) Huang*, Bruce Herr* & Ben Markines+ *School of Library and Information Science +Department of Computer Science Indiana University, Bloomington, IN

Network Workbench ( Project Details Investigators: Katy Börner, Albert-Laszlo Barabasi, Santiago Schnell, Alessandro Vespignani & Stanley Wasserman, Eric Wernert Software Team:Lead: Weixia (Bonnie) Huang Developers: Bruce Herr, Ben Markines, Santo Fortunato, Ramya Sabbineni, Vivek S. Thakre, Russell Duhon & Cesar Hidalgo Goal: Develop a large-scale network analysis, modeling and visualization toolkit for physics, biomedical, and social science research. Amount:$1,120,926, NSF IIS award Duration: Sept Aug Website:

Network Workbench ( Project Details cont. NWB Advisory Board: James Hendler (Semantic Web) Jason Leigh (CI) Neo Martinez (Biology) Michael Macy, Cornell University (Sociology) Ulrik Brandes (Graph Theory) Mark Gerstein, Yale University (Bioinformatics) Stephen North (AT&T) Tom Snijders, University of Groningen

Network Workbench ( Major Deliverables Network Workbench (NWB) Tool oA network analysis, modeling, and visualization toolkit for physics, biomedical, and social science research. oCan install and run on multiple Operating Systems. oUses Cyberinfrastructure Shell Framework underneath. NWB Community Wiki oA place for users of the NWB Tool, the Cyberinfrastructure Shell (CIShell), or any other CIShell-based program to request, obtain, contribute, and share algorithms and datasets. oAll algorithms and datasets that are available via the NWB Tool have been well documented in the Community Wiki. Cyberinfrastructure Shell (CIShell) oAn open source, software framework for the integration and utilization of datasets, algorithms, tools, and computing resources.

Network Workbench ( Integrating and Implementing Algorithms Modeling and Network Generation Random Network Model Random Preferential Attachment Algorithms Barabasi-Albert Model Dorogovtsev-Mendes-Samukhin Fitness Vertices/edges deletion Copying strategy Finite vertex capacity TARL Rewiring algorithms Rewiring based on degree distribution Watts Strogatz Small World Model Peer-to-Peer Models Structured CAN Model Chord Model Unstructured PRU Model Hypergrid Model Statistical Measurement Edge/Node level node degree BC value of nodes/edges Max flow edge Hub/Authority value for nodes Distribution of node distances (Hop plot) Local (directed and weighted versions) Clustering Coefficient (Watts Strogatz) Clustering Coefficient (Newman) k-Core Count Distributions (Plot and gamma, and R^2) Degree Distributions (in, out, total) (Directed/TotalDegree Distribution) Degree Correlations (in-out, out-out, out-in, in-in, total-total) Clustering Coefficient over k Coherence for weighted graphs Distribution of weights Probability of degree distribution Global Density Square of Adjacency Matrix Giant Component Strongly Connected Component Betweenness Centrality Diameter Shortest Path = Geodesic Distance Average Path Length Motif Identification Page Rank Closeness centrality Reach centrality Eigenvector centrality Minimum Spanning Tree

Network Workbench ( More Algorithms Searching on Networks Search k Random-Walk Search Depth First Search p-rand Breadth-First Search P2P CAN Search Chord Search Epidemics Spreading SIR SIS Clustering on Networks Based on Attributes Hierarchical Clustering Single Link Complete Link Average Link Ward's Algorithm Based on Network Structure Newman Girvan Clauset-Newman-Moore Newman Cecconi-Parisi Simulated annealing of modularity Caldarelli Weak Component Clustering vanDongen (random walk) Cfinder (Clique percolation method) Reichardt, Bornholdt (q-potts model) Graph Matching On Networks Simple Match Similarity Flooding ABSURDIST Visualization of Networks Distribution Scatterplot Histogram Geospatial Circle layout Grid-based Dendrogram Treemap Hyperbolic tree Radial Tree Sparse Matrix Visualization Kamada-Kawaii Fruchterman-Rheingold Orthogonal Layout k-core visualization

Network Workbench ( Outline oDemonstrate the functions provided by the current version of NWB Tool oPresent the underlying technologies supporting those functions – NWB/CIShell architecture oHighlight the features in NWB Community Wiki oDiscuss the future work

Network Workbench ( NWB Tool Major Deliverables Major features in v0.2.0 Release oInstalls and runs on Windows and Linux x86. oProvides over 40 modeling, analysis and visualization algorithms. Half of them are written in Fortran, others in Java. oProvides several sample datasets including 9-11 terrorist network, NetSci06 conference attendee network, etc. oSupports the loading, processing and saving of four basic file formats: GraphML, Pajek.net, XGMML and NWBNWB oIntegrates a 2D plotting tool -- xmgrace on Linux. New features in the coming v0.3.0 Release (Dec 21 st, 2006) oSupports to run on Mac OSX. oMakes xmgrace work on windows oImplements Scheduler GUI oAdds new algorithms: TARL, Pathfinder Network Scaling, etc. oImproves existing modeling, analysis, and visualization algorithms. Download from

Network Workbench ( NWB Tool – Algorithms (Implemented) CategoryAlgorithmLanguage PreprocessingDirectory Hierarchy ReaderJAVA Modeling Erdös-Rényi RandomFORTRAN Barabási-Albert Scale-FreeFORTRAN Watts-Strogatz Small WorldFORTRAN ChordJAVA CANJAVA HypergridJAVA PRUJAVA Visualization Tree MapJAVA Tree VizJAVA Radial Tree / GraphJAVA Kamada-KawaiJAVA Force DirectedJAVA SpringJAVA Fruchterman-ReingoldJAVA CircularJAVA Parallel Coordinates (demo)JAVA ToolXMGrace Analysis AlgorithmLanguage Attack ToleranceJAVA Error ToleranceJAVA Betweenness CentralityJAVA Site BetweennessFORTRAN Average Shortest PathFORTRAN Connected ComponentsFORTRAN DiameterFORTRAN Page RankFORTRAN Shortest Path DistributionFORTRAN Watts-Strogatz Clustering CoefficientFORTRAN Watts-Strogatz Clustering Coefficient Versus DegreeFORTRAN Directed k-Nearest NeighborFORTRAN Undirected k-Nearest NeighborFORTRAN Indegree DistributionFORTRAN Outdegree DistributionFORTRAN Node IndegreeFORTRAN Node OutdegreeFORTRAN One-point Degree CorrelationsFORTRAN Undirected Degree DistributionFORTRAN Node DegreeFORTRAN k Random-Walk SearchJAVA Random Breadth First SearchJAVA CAN SearchJAVA Chord SearchJAVA

Network Workbench ( NWB Tool: Demo Load DataList of Data Models Scheduler Open Text Files Console Visualize Data Select Preferences

Network Workbench ( NWB Tool – Data Formats Converters and Conversion Services Between Various Data Formats

Network Workbench ( Three User Groups Application Users oScientists in the natural and social sciences (physics, biology, chemistry, psychology, sociology, etc.) oTheir needs -- want to find the best datasets and the most effective algorithms to conduct their research. oProblem – too many algorithms. Finding a correctly working piece of code is challenging. Frequently, not only one but a sequence of different algorithms needs to be applied to load, parse, clean, mine, analyze, model, visualize, and print data. Today, there is no easy way to extend a tool by adding new algorithms as needed or to customize a tool so that it exactly fits the needs of a specific user (group).

Network Workbench ( Three User Groups (cont.) Application Designers oComputer scientists or application users that developed the applications and tools we use today. oThey usually start by developing applications/tools that meet their own needs, and then generalize them to satisfy the requirements of their research community. oChallenge -- not only need to take care of the software architecture, the GUI design, the development of many basic components and functions, but also play the role of algorithm developers.

Network Workbench ( Three User Groups (cont.) Algorithm Developers oComputer scientists, statisticians and other researchers oThey look for opportunities to disseminate their work and test the practical utilities of their algorithms. oChallenge -- the integration of a dataset or algorithm into an existing application or tool requires a deep understanding of the architecture of that application, which is non-trivial.

Network Workbench ( OSGi – Technical Details NWB/CIShell is built upon the Open Services Gateway Initiative (OSGi) Framework. OSGi ( ishttp:// oA standardized, component oriented, computing environment for networked services. oAlliance members include IBM (Eclipse), Sun, Intel, Oracle, Motorola, NEC and many others. oHas successfully been used in the industry from high-end servers to embedded mobile devices for 7 years now. oWidely adopted in open source realm, especially since Eclipse 3.0 that uses OSGi R4 for its plugin model. Advantages of Using OSGi oDirectly use many components provided by OSGi framework, such as service registry oContribute diverse algorithms to OSGi community -- any CIShell algorithm becomes a service that can be used in any OSGi-based framework. oRunning CIShells/tools can connect to each other via exposed CIShell-defined web services supporting peer-to-peer sharing of data, algorithms, and computing power. Ideally, CIShell becomes a standard for creating algorithm services in OSGi developed Tools/CI, e.g., IVC&NWB will be using the CIShell reference GUI

Network Workbench ( NWB/CIShell is built upon the Open Services Gateway Initiative (OSGi) Framework OSGi – Technical Details

Network Workbench ( An Overview of NWB/CIShell Architecture NWB/CIShell Architecture cont.

Network Workbench ( An Abstract Definition of Algorithms, Datasets and Converters Interfaces Layer – Algorithm

Network Workbench ( Basic Algorithm APIs Interfaces Layer – Algorithm cont. public interface AlgorithmFactory { public MetaTypeProvider createParameters(Data[] data); public Algorithm createAlgorithm( Data[] data, Dictionary parameters, CIShellContext context); } public interface Algorithm { public Data[] execute(); } Advanced Algorithm APIs (optional) DataValidator and ProgressTrackable Interfaces

Network Workbench ( Basic Algorithm APIs Templates public interface AlgorithmFactory { public MetaTypeProvider createParameters(Data[] data); public Algorithm createAlgorithm( Data[] data, Dictionary parameters, CIShellContext context); } public interface Algorithm { public Data[] execute(); } Advanced Algorithm APIs (optional) DataValidator and ProgressTrackable Interfaces

Network Workbench ( oPreferences Service oLog Service oData Conversion Service oGUI Builder Service Interfaces Layer – Basic Services Basic Services

Network Workbench ( oScheduler Service oData Manager Service Interfaces Layer – Application Services Application Services

Network Workbench ( oCIShellContext oData Interfaces Layer – Other Components Other Framework Components

Network Workbench ( Services Layer – Basic Services oPreferences Service oLog Service oData Conversion Service oGUI Builder Service Basic Services

Network Workbench ( oScheduler Service oData Manager Service Services Layer – Application Service Application Services

Network Workbench ( oCIShellContext - LocalCIShellContext oData - BasicData Services Layer – Other Components Other Framework Components

Network Workbench ( Application Solutions Reference GUI (using Eclipse RCP) oFramework View oData Manager View oConsole(log) View oScheduler View oMenu Manager

Network Workbench ( Other application solutions Application Solutions cont.

Network Workbench ( NWB Tool oAnalyze, visualize and model network/graph oSupport most popular data formats and data conversion among them oServe three communities with different practices Applications

Network Workbench ( Biological Networks Portal oUse Web front-end solution oFor educational purpose Applications cont.

Network Workbench ( Algorithm Developers Need to Know For Algorithm Developers (Java-based) oMust implement CIShell Algorithm APIs oKnow how to use Basic Serivces APIs, Application Serivces APIs, CIShellContext, and Data APIs, but don’t need to take care of the detail implementations of those services or components. Need to change diagram and show templates

Network Workbench ( Component Level oUsing OSGi service implementations from different vendors oEach service/component can have more than one implementations Application Designers Need to Know

Network Workbench ( Application Designers Need to Know Framework Level oUse all implementations of algorithms and converters oUse all implementations on the service layer oConcentrate on application solutions oUse or refer to the reference implementations of an application

Network Workbench ( oGet the most efficient algorithm implementations oGet as many algorithms as needed oHave tools running on multiple platforms and various application solutions oDon’t worry about the match between the data format of a dataset vs. algorithm input Application Users

Network Workbench ( Community Wiki

Network Workbench ( Community Wiki cont.

Network Workbench ( Future Work Add features to serve communities including Physics, Biology, Social Science, and Scientometrics. oIntegrate classic datasets oSupport the most popular data formats for biology and social science research. oDevelop the converters to bridge those formats to the current formats supported by NWB tool. oDesign and deliver better visualization algorithms and modularity oDevelop components to connect and query SDB oCustomize Menu – Users can re-organize the algorithms for their needs oContinue integrating best algorithm implementations

Network Workbench ( Acknowledgement We would like to acknowledge the NWB team members that made major contributions to the NWB tool and/or Community Wiki: Santo Fortunato, Katy Börner, Alex Vespignani, Soma Sanyal, Ramya Sabbineni, Vivek S. Thakre, Russell Duhon, Elisha Hardy, and Shashikant Penumarthy. We are working with Albert-Laszlo Barabasi, Cesar Hidalgo, Stanley Wasserman, and Ann McCranie to refine the requirements and plan new features to meet the needs of biologists and social scientists.

Network Workbench ( Comments & Questions Thank you