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Making Workflows Work Prof. Yike Guo Dept. of Computing Imperial College London InforSense Limited DiscoveryNet Project Funding One of the Eight UK National e-Science Projects (£2.2 M) Sept 2001 – March 2005 Partners Achievements Constructing the World’s First Infrastructure for Building Analytical Services by Scientists For the First time Discovery Net Realises the Dynamic Construction of Compositional Services on GRID for Real Time Knowledge Discovery and Decision Making Outputs Software Research: DNet platform commercialized by InforSense Ltd (>100 customers) Total user numbers > 2000 Applications Research: Application out puts in sensor technology commercialized by deltaDot Ltd Number papers published: 10 Journal Papers, 30 Conference Papers 8 PhD completed and 50 Master students Ranked OUTSTANDING at the project final review Proprietary and Confidential InforSense Introduction 100+ customers (70% Fortune 200 companies) 2006 3rd fastest growing company in UK (Sunday Times Tech Track) 2007 8th fastest growing venture-based company in UK (Financial Times) Global footprint with offices in London (HQ and R/D), Boston (USA HQ) and Shanghai (Asia HQ and Development base) Global sales with 70% outside of Europe 7 years of delivering products and services to pharmaceutical and Financial industries Spin out from Imperial College London Innovation in Embedding Analytics InforSense Formed Introduced ‘00 KDE Analytics Platform Invented “ ‘98 Distributed Data Mining ” Proprietary and Confidential Discovery Net ‘01 Project Embedding Analytics Technology ‘053rd fast growing company in UK IEEE Supercomputing Award – ,03 Grid based analytics First 2004 Enterprise Deployment ‘06 Embedding Analytics in Major Enterprise Systems Those who are using our workflow CAMBRIA BIOSCIENCES Proprietary and Confidential InforSense Workflow Methodology Portal / Dashboard Application Delivery to End User Business Process Administrator Clinician Disease Biologist Rapid Application Deployment Integrative Analytics Workflow Environment Automation & Scheduling Interactive Solution Building Interactive Knowledge Discovery Dynamic Data & App Integration Data Applications InforSense Analytics Oracle Pre-processing 3rd party Analytics Web services Biomedical Informatics tools Multiple data sources Components Files Proprietary and Confidential EMR Databases Excel What is InforSense WF System Designed for ? InforSense workflow system is not an application but a framework to build and deliver applications directly to scientist/business user: ADMET Browser Chem-Studio Proprietary and Confidential InforSense Generic Workflow Engine Pipelining Simulation & Modelling Business Process Managenment Web Service Orchestration ETL Data/Text Mining Enterprise Service Bus Proprietary and Confidential Experience of 7 years in WF business Building workflow is easy ! However, Building a USABLE workflow is not easy Building a REUSABLE workflow is hard Building a REUSABLE workflow applications is very hard Building a REUSABLE workflow application for EVERYONE is very very hard Building a function is easy, building an application is hard, it is even harder if we enable a non-IT person to build a good reliable application for other people to use everyday! Proprietary and Confidential InforSense Workflow System Development Native MPI Condor-G OGSA-service Web Service Resource Mapping Workflow Embedding Web Wrapper Sun Grid Engine Pervasive WF applications Oralce 10g Unicore Workflow Execution Workflow Warehousing Reliable Enterprise Wide Execution Workflow Authoring Composing services Service Abstraction Workflow Management Collaborative Knowledge Management Proprietary and Confidential Workflow Deployment: Building Reusable WF Applications Three Tiers of Workflow Framework Service Orchestration Embedding Layer Business Rules BPEL Application Layer Embed in Other Applications Analytic Service Encapsulation Publish Services for Display Analytical Workflow Development Building Layer Proprietary and Confidential Rapid Application Development InforSense Workflow Building: Not about another graph notation but about how to build a meaningful graph Current model of workflow authoring/execution No help provided to user (authoring/execution) Model is based on expert user who know about services Model requires user to be trained in a workflow language/system Interoperability between workflow systems is only at run-time Proprietary and Confidential The key the success : End User Oriented Workflow Construction Build semi-automatic tools that advise/assist user in wf authoring Make use of previous knowledge about developing workflows Explicit/Expert knowledge Implicit knowledge in previous workflows The aim is to help user, not replace him Proprietary and Confidential Guided Workflow Construction User is presented by high-level descriptions of predefined task steps User is guided iteratively in instantiating the task descriptions using workflow templates User can retrieve workflows and workflow templates from repository Approach supports using workflows from multiple systems using existing run-time interoperability mechanisms Proprietary and Confidential Workflow Advisor: InforSense Customer Hubs Proprietary and Confidential Extended infrastructure: Workflow warehousing and mining Workflow Advisor Initial implementations of prototype for bio applications Workflow Assistant Abstract component initial prototypes Workflow Mining Repository of workflows from Southampton Workflow Annotations independent from workflow language Warehouse Search and execute web services/Grid services and workflows Syntactic and semantic search Proprietary and Confidential Extended infrastructure: Workflow warehouse/registry Proprietary and Confidential InforSense Embedding and Deployment Workflow output is not a data, but an application/service InforSense KDE Deployment Strategies Deploy workflows to InforSense portal Deployment features: multi-page, service chain, layout editor Multi-stage applications: group workflows into stages Component based deployment Portlet based deployment Portlet component: JSR 168 compatible portlet components Business process workflow Based on control flow orchestrated workflows and role based deployment Proprietary and Confidential Web-based Deployment Portal Container allows users to build dashboards Each Workflow generate data for a dashboard component Workflow results viewed in simple charts - can be linked to other pages Proprietary and Confidential Deployment Features (2) Define multiple pages Move to next page Proprietary and Confidential Example Application Chip QC Analytical stage Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Results QC Step n ru Re t1 t es QC t 1 tes QC t 1 t es QC t 1 tes QC t 1 t es QC t 1 tes QC t 1 t es t1 t es QC Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Submit to Report> QC Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Slide 1 Slide 2 Slide 3 Next Steps Slide 4 Slide 5 WorkflowSlide configured 6 to group according to stage Proprietary and Confidential Chip must be rerun Recommended rerun Normalisation services •RMA (recommended) •LiWong •ETC Portal look and feel can be customized by style sheet Example Application Chip QC Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Submit to Report> Results Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Next Steps Analysis services •Volcano Plot (recommended) •PCA •Dendrogram Proprietary and Confidential Example Application Chip QC Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Submit to Report> Results Save Result to Report Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Next Steps Analysis services •Select Transcripts •Filter Data Proprietary and Confidential Example Application Chip QC Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Submit to Report> Results Save Selected Items to Report Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Next Steps Interpretation services •Send Data to Ingenuity •Send Data to Gene Go •Send Data to •Text Analysis Proprietary and Confidential Example Application Chip QC Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Submit to Report> Results Save to Report Related Pathway Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Next Steps Interpretation services •Send Data to Gene Go •Text Analysis Proprietary and Confidential Example Application Chip QC Normalise Analyse Interpret Design Experiment Design Study groups for transcriptomics portal Gene Expression Profiling Pre-process and Analyse the results of a gene expression analysis to compare control vs. test populations Submit to Report> Select Subset for Text Analysis Results Related Pathway Splice Variance Analysis Pre-process and Analyse the results of an Exon Chip to find differences in splice variance between control vs. test populations Next Steps Interpretation services •Send Data to Gene Go •Text Analysis Proprietary and Confidential Business Process Workflow (1) Business Process Management Development A Business Process Management (BPM) describes the orchestration of different tasks to complete a specific business objective Business Processes need to orchestrate Automated Tasks User Tasks Exception Handling Running Tasks in parallel Synchronisation of parallel tasks Proprietary and Confidential Business Process Workflow (2) InforSense Control Flow InforSense Control Flow for Orchestrating Workflows for Business Process Run Task Initiate Parallel Tasks Handle Exceptions Proprietary and Confidential Apply Rules Synchronize Parallel Tasks Business Process Workflow (3) Orchestra business analytics by control flow Control Flow Represents a Business Process Process Building Blocks Deploy to Portal Sub-process 1 Workflow A Sub-process 2 Workflow B Workflow C definition of linkage/control and user interactions Application Building Blocks services Proprietary and Confidential Workflow interoperability Workflows and business processes (BPEL) Proprietary and Confidential Embedding Workflow Analytics into Applications Process View Embeddable Analytic Applications Analytical Workflows customer data Get Value Score Get Churn Score Churn Service Predictive scores Lifetime Value Service Risk data Risk Service Risk Assessment Risk Evaluation KVM Acceptable Risk? No Deploy New Actions Yes Normal Service Upgrade offer Model Repository Business Rules and Model Proprietary and Confidential Integrating Analytics with Business Rules: Adaptive Business Process Business Process Business operational data Proprietary and Confidential Rule engine Rule Engine Enterprise Services Bus Analytics to drive adaptive processes Business Portal Embedding with Applications InforSense Tools as one item in Windows based application system Proprietary and Confidential Proprietary and Confidential Making Workflow Work “One of the biggest barriers to achieving productivity and responsiveness is IT – it has become a bottleneck. Another barrier to achieving the goal is the lack of intelligence that drives most IT applications. They are just operating as a rapid functional replacement, and failing to exploit the data which is being generated within other elements of the IT infrastructure. A product that could meet that challenge and enable business to generate and deploy intelligence with speed, accuracy and without the need for specialized skills would be remarkable. I believe that InforSense is that remarkable tool.” -- David Norris, Senior Analyst, Bloor Research Proprietary and Confidential Thank You ! Proprietary and Confidential