1. Hassan A. Karimi Geoinformatics Laboratory School of Information Sciences University of Pittsburgh 3/27/20121

2. Outline Key findings of the SBE VISION 2020 (Rebuilding the MOSIAC) report World-Historical Dataverse and the SBE VISION 2020 report World-Historical Dataverse Research Challenges 3/27/20122

3. SBE VISION 2020: Rebuilding the MOSIAC Fostering Research in the Social, Behavioral, and Economic Sciences (SBE) at the National Science Foundation in the Next Decade National Science Foundation, Directorate for Social, Behavioral and Economic Sciences (2011) 3/27/20123

4. SBE VISION 2020: Topics “Important questions (the fundamental science questions)” “Data and infrastructure (data-intensive science, methodologies, research centers, shared toolkits, and so on)” “Capacity building (education and training of graduate students, faculty, and systems of prestige, promotion, and recognition)” 3/27/20124

5. SBE VISION 2020: What Is Collaborative Research? “The notion of collaborative research teams is one way that data-intensive SBE research implies a shift away from the independent, single investigator/small team model of scientific research.” 3/27/20125

6. SBE VISION 2020: Next Generation SBE Research Research MultidisciplinaryData-IntensiveCollaborative Mediated by Technology Problem Focused 3/27/20126

7. World-Historical Dataverse: Multidisciplinary Research Ontologies Conceptualizations of problems/scenarios within and across disciplines Data Collected and contributed by researchers from different disciplines Public health, geology, economics, geography, anthropology,… Models Social sciences, information science, computer science,… Analysts Scientists, researchers, students,… 3/27/20127

8. World-Historical Dataverse: Data- Intensive Research Large-Scale Data CollectionOrganizationStorageProcessing 3/27/20128

9. World-Historical Dataverse: Collaborative Research Share DataToolsAnalyticsVisualizations 3/27/20129

10. Research Challenge: Data Data Model A unified space-time data model that integrates Heterogeneous data sources Structured and unstructured data Data Analysis Understanding data through visualization 3/27/201210

11. Research Challenge: Data-Intensive Storage Distributed data repository Efficient processing Supercomputers Grids Clouds Visualization Adaptive maps 3/27/201211

12. Research Challenge: Collaboration A cyberinfrastructure platform that facilitates Identification and connection of the analysts needed to solve a given a problem automatically Resource sharing Collaborative visualization Collaborative problem solving 3/27/201212

13. Research Challenge: Analytics Simulation of data- and compute-intensive problems/scenarios Knowledge discovery through connection of data/scenarios across disciplines Predication methodologies, models, and techniques 3/27/201213