Laura Haas, IBM Fellow IBM Research - Almaden From Data to Foresight: Leveraging Data and Analytics for Materials Research 1 2011 IBM Corporation
The road from data to foresight is long? Consumer Reports How can I reduce my? Must acquire, integrate, enhance and align Must deal with missing and incomplete data Must store, protect, and manage Must create models and other analytics and test them Must run these analyses efficiently over large data volumes Must understand and share results INPUT SATURATION & SATURATION SURFACE RUNOFF & SURFACERunoff SURFACE Runoff Saturated Surface Area Runoff MISCELLANEOUS Observed MISCELLANEOUS Precipitation MISCELLANEOUS FLUXES MISCELLANEOUS MISCELLANEOUS FLUXES FLUXES FLUXES FLUXES INTERFLOW INTERFLOW Percolation Misc OVERLAND OVERLAND fluxes ROUTING PERCOLATION ROUTING PERCOLATION PERCOLATION Interflow Instantaneous Effective Runoff RAINFALL RAINFALL Precipitation Routed Runoff ERROR ERROR Percolation Total Water: SOLVE Upper Layer, SOLVE STATE EQUATIONS SOLVE UPDATE SOLVE UPDATE Lower Layer STATE UPDATE STATE EQUATIONS SOLVE UPDATE STATE EQUATIONS STATE OUTPUT STATE UPDATE Lower STATE EQUATIONS EQUATIONS STATE STATE Layer Evaporation LOWER LOWER LAYER LOWER Layer LOWER Layer EVAPORATION Layer EVAPORATION Baseflow Potential EVAPORATION Evapo- Transpiration BASE BASE FLOW BASE FLOW BASE FLOW Upper BASE FLOW FLOW Layer UPPER UPPER LAYER Evaporation UPPER LAYER EVAPORATION UPPER LAYER LAYER EVAPORATION EVAPORATION Legend: Flux computations Inputs and outputs State computations Note: in addition to dependencies shown, most flux calculations are dependent on values of state variables at the previous timestep Requires significant (and expensive) EXPERTISE in data management, systems, analytics, and the domain Takes TIME 2 2011 IBM Corporation
The 4 V s of data Volume Velocity Variety Veracity* * Truthfulness, accuracy or precision, correctness Data at Rest Data in Motion Data in Many Forms Data in Doubt Terabytes to exabytes of existing data to process Streaming data, milliseconds to seconds to respond Structured, unstructured, text, multimedia Uncertainty due to data inconsistency & incompleteness, ambiguities, latency, deception, model approximations 3 2011 IBM Corporation
Valuable new insights are hidden in this wealth of data! Detect life-threatening conditions at hospitals in time to intervene Predict weather patterns to plan optimal wind turbine usage, and optimize capital expenditure on asset placement Make risk decisions based on real-time transactional data Identify criminals and threats from disparate video, audio, and data feeds Discover and optimize new materials by mining data in the patents and literature 4 2011 IBM Corporation
Fortunately, new platforms can unlock the value of data New analytic applications drive the requirements for a big data platform BI / Reporting Analytic Applications Exploration / Visualization Functional App Industry App Predictive Analytics Content BI / Analytics Reporting Integrate and manage the full variety, velocity and volume of data Apply advanced analytics to information in its native form Visualize all available data for adhoc analysis Develop new analytic applications Optimize and control scheduling of many simultaneous analyses Protect data and applications from accidents, sabotage, and theft Visualization & Discovery Hadoop System IBM Big Data Platform Application Development Accelerators Stream Computing Systems Management Data Warehouse Information Integration & Governance 5 2011 IBM Corporation
Outcome-based medicine vision: Leverage public and private content, rich analytics to improve treatment outcomes Target Identification Target Selection Lead Discovery Candidate Selection Preclinical Development Development Selection Clinical I II IIIl Launch Medical Care Patient Experience Patient Outcome Research & Development and Intellectual Property Target Identification and Validation Lead Discovery and Optimization Safety and Efficacy Genomics Proteomics Metalobomics Chemical and Biological Extraction, Profiling, Analytics, And Reasoning Clinical Decision Support Patient Similarity and Segmentation Patient Cohorts for Clinical Support Clinical Genomics Analysis Comparative Effectiveness Research Predictive Modeling of Outcome Disease Progression Analysis Treatment Cost Analysis Temporal Analysis Patient experience and social community support Patient first hand experiences Social community development and support Key Analytics Capabilities: BI, Text analytics, NLP, Network Analysis, Relationship Discovery, ML, Modeling, High Scientific Ontologies Safety Electronic Throughput Patents Pre-clinical Literature Pathways DMPK Medical Web Claims Data Screening Curated Data Formulation Clinical Trials Records Social Media 6 2011 IBM Corporation
An Example: Leveraging data to accelerate life sciences R&D The Situation Highly volatile, increasingly complex environment Traditional R&D is not delivering New approaches are needed Collaborative R&D models The new normal requiring open platforms, clear boundaries and protection Agile responses Vital to drive fast adaptation to changing competitive IP landscape including, adjustments to strategy, portfolio investments and partnerships Effective IP portfolio management Delivering key value for out-licensing and monetizing of non-core IP Strategic ecosystem development Growth and competitive differentiation through aggressive collaboration, early identification of acquisition and recruitment targets The Solution IBM BAO strategic IP insight platform (SIIP) A unique and powerful data and analytics offering Aggregates and processes 30M+ patents and scientific literature from around the globe Automatically extracts chemical and biological entities 200M+ chemical compound instances to date Generates chemical and biological entity profiles Searches and analyzes using natural language-based inputs for key relationship discovery and IP insights Reasoning about causality of drug, diseases, targets, and efficacy and side effects Integrates and enhances existing data and applications The Benefits Valuable insights into competitive landscape, white space, and IP portfolio High quality chemical extractions available hours after patents are available from patent authorities Previously unobtainable insights at the scientists fingertips with the touch of a button Fast and easy search and analysis drastically reducing search time from weeks and months to just minutes R&D Find white space and gain insight into complex chemical and biological patents; Gain early insights into given targetcompound match from past patents for better research target & compound selection decisions Legal Detect IP infringement earlier and increase the quality of patent filings Corporate Strategy / Business Dev Identify collaboration and acquisition targets for greater research value and effectiveness and find patent in- and out licensing candidates for efficient management and monetization of IP 7 2011 IBM Corporation
A Smart Entity Profiling, Analytics and Reasoning Methodology IP - Legal status - Assignee - Foreign filings - Expiration Date An integrated framework leveraging broad set of data, and many types of analytics: Hypothesis generation Entity extraction and profiling Relationship discovery and analytics Summarization Reasoning Scoring and ranking Predictive modeling Key steps: Extract key entities Combine information from multiple sources Discover relationships among entities Reason about relationships Drug - Activity - Half life - Protein Binding Disease Organisms - Organism - Organ - Cell - Tissue Physical - Computational - Molecular Weight - MF, Bp, Mp Medicine Pathways - Metabolic - Genetic - Environmental - Cellular - Organism Spectral - IR - NMR - Mass Spectra Patients Genetic -... Medical Records -... Reactions - Enzymes Life styles -... Toxocity - Clinical Trials - Pre-Clinical Screening - Activity Medical History -... Patents Literature Experimental HTS Medical Records Clinical Business Social 8 2011 IBM Corporation
Information and Governance for Big Data Leverage private/public clouds to share vs keep proprietary as appropriate 9 2011 IBM Corporation
Summary There is much to be gained from leveraging available data and content Accelerate discovery Avoid repeating work Unlocking the value buried in there is difficult 4 V s: Volume, Velocity, Variety, Veracity A long process requiring many types of expertise There are powerful platforms and tools that can help Aid development of type-specific analytics Enable fast and timely processing of large diverse data sets Sharing, with appropriate data governance, can accelerate discovery Controls for the entire data lifecycle Many industry groups are finding leverage from shared investments 10 2011 IBM Corporation