IBM Solution Framework for Lifecycle Management of Research Data IBM Corporation

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1 IBM Solution Framework for Lifecycle Management of Research Data

2 Aspects of Lifecycle Management Research Utilization of research paper Usage history Metadata enrichment Usage Pattern / Citation Collaboration / sharing Data Management Access security Right and privileges Digital Asset Management Stewardship / Data Curation Storage Management Tiered storage Archiving Digital preservation Data Storage / centralize vs decentralize Discarding / disposition 2

3 Current Challenges - Research & Publishing Volume, velocity, & variety Discrete rights management Metadata management Reusability / Transformation Analytics Real time analytics Knowledge Management and Insight Search Optimization Long term preserving of voluminous data Cloud / SaaS Infrastructure Real time computation / scientific data 3

4 IBM s Media Enterprise Framework provides SW capabilities to meet the needs of an agile media, research and publishing company Interaction Media Integration Enterprise Framework Media Business Domains Content Production Digital Workflow Transformation Enterprise Metadata Management (EMM) Content Distribution Editorial Media, Metadata and Information Management Web-Centric Business Innovation Web Analytics Multi-Channel Enablement Global Media Social Media Media Monitoring & Analytics Collaboration Content Analytics & Insight Business Systems Enterprise Asset Management Enterprise Master Data Management Enterprise Data Warehouse Business Process Transformation Application Integration Data Integration Infrastructure Management & Security Service Orientated Architecture Information Architecture IT Infrastructure

5 IBM Smart Archive Strategy Lifecycle Management Reports ERP / CRM (SAP, PeopleSoft ) Content (Documents, Images ) Paper Collaborative (Quickr, SharePoint) Data (Notes, Exchange) Value Added Services Optimization Services System Services Managed Services Reference Architecture Information Governance Optimized and Unified Assessment, Collection and Classification On Premise (Custom Config) Flexible and Secure Infrastructure with Unified Retention and Protection Appliance (Pre-Config) As A Service (SaaS, Multiple Options) Cloud Ready Archive Storage with Optional ECM Integrated Compliance, Records Management, Analytics and ediscovery 5

6 IBM s Big Data Platform Vision Bringing Big Data to the Enterprise IBM Big Data Solutions Client and Partner Solutions Big Data User Environments Developers End Users Administrators Data Warehouse InfoSphere Warehouse Warehouse Appliances Netezza Master Data Mgmt AGENTS Big Data Enterprise Engines INTEGRATION InfoSphere MDM Database DB2 Analytics Streaming Analytics Internet Scale Analytics SPSS Business Intelligence Open Source Foundational Components Hadoop MapReduce HDFS Hbase Pig Lucene Jaql Cognos Marketing Unica

7 What makes IBM different? IBM has over 25+ years of experience in the area of Enterprise Media and Publishing with large deployments across many of the leading companies in the Media, research and publishing market In the media, research and publishing space, IBM has actively participated and is committed to create standards in the creation, management, and preservation of rich media content such as high resolution images, videos, audio, compound documents, etc. IBM has established a media framework that incorporates SOA Interoperability Standards and addresses all aspects of media management; Abstract Service Definition for Media Services (ASD) that supports MPEG21 and rich metadata content; and Enterprise Service Bus ESB with a media extension called Media Hub. IBM has developed standards in the area of digital preservation especially to address usability of content stored on an obsolete system. To address the issue of keeping digital content for very long period of time despite technology obsolesce, IBM has invented a Long Term Digital Preservation (LTDP). Long Term Digital Preservation (LTDP) is a means of keeping digital information so that the same information can be used in the future despite obsolescence of everything involved: hardware, software, processes, format, people, etc. LTDP is particularly challenging when preserving large amounts of heterogeneous data for very long periods of time over tens or even hundreds of years, based on interoperability standards.

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