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An Information Architect's View of Earth Observations for Disaster Risk Management NH11B-3708 We focus on the need to develop actionable information products.

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Presentation on theme: "An Information Architect's View of Earth Observations for Disaster Risk Management NH11B-3708 We focus on the need to develop actionable information products."— Presentation transcript:

1 An Information Architect's View of Earth Observations for Disaster Risk Management NH11B-3708 We focus on the need to develop actionable information products from these Earth observations to simplify the discovery, access and use of tailored products. The information architecture can address usability challenges to transform sensor data into actionable information, based on the terminology of the emergency management community responsible for informing the public. This paper describes the approach to collecting relevant material from the disasters and risk management community to address the end user needs for information. The resulting information architecture addresses the structural design of the shared information in the disasters and risk management enterprise. Key challenges are organizing and labeling information to support both online user communities and machine-to-machine processing for automated product generation. Abstract Background: Satellite observations play a significant role in supporting disaster response and risk management, however data complexity is a barrier to broader use especially by the public. In December 2013 the Committee on Earth Observation Satellites Working Group on Information Systems and Services documented a high-level reference model for the use of Earth observation satellites and associated products to support disaster risk management within the Global Earth Observation System of Systems context. The enterprise architecture identified the important role of user access to all key functions supporting situational awareness and decision-making. User-generated postings Routine / Global Monitoring 1. Event detection Routine / Global model outputs Task sensors In situ Remote Acquire data 3. Data acquisition Archive Visualize Ongoing updates Alerts / Notices Publish product 6. Dissemination Preproces s Analyze 5. Analysis Interpret 4. Modeling Forecast Hindcast Nowcast 2. Situational Awareness Gather / Assimilate Information Decision Analysis: Act / Plan Initiators Processors Actuators Coordinators 7. User Access Activities in Satellite Disaster Management Architecture in·for·ma·tion ar·chi·tec·ture n. Definition The art and science of shaping information products and experiences to support discovery and use Structural design of shared information environment, i.e., information spaces, to help users find answers, complete tasks Not data and knowledge management Practice: Understand and leverage relationships between Users needs, tasks, experience Content types, objects, size/complexity of products &services Context within goals, culture, resources, constraints Information Architecture Source: www.bruceclay.com Basic concepts Information (content) Metadata (terms used to describe and represent content objects) Structure (content and relationships) Organization (meaningful categories) Labels (naming conventions, controlled vocabularies) Discovery (ability to find what you want) Usage patterns (analysis of user needs and behaviors) Framework (facilitates access to content and services) Benefits Reduce cost of finding information Educating users about products and services Reduce cost of building and maintaining products and services Develop a community and a brand The Envirocast® Vision™ Collaboration Module (EVCM) Source: StormCenter Communications, Inc. Disaster Life Cycle Source: www.ceos.org/ Radarsat2 Detected Water Extent Composite Flood Extent Data Product (Haiti 8/25/12) OpenStreetMap Normal Water Baseline Community Collaboration Disaster Lifecycle Information Architecture Goals Assure timely delivery of useful Earth observations to decision makers as well as analysts and forecasters. Streamline access to products. Lower barriers to entry for users and suppliers. ESIP Disaster Lifecycle Cluster Purpose: Facilitate connections and coordinate efforts among data providers, managers and developers of disaster response systems and tools, and end-user communities within ESIP. Activities: Share insights and best practices 1) on user needs, common procedures, common barriers 2) translate needs into system architecture practices. Explore emerging technologies and match to needs. Bridge the gap between developers and users. Collaborative Common Operating Picture (C-COP) Testbed: Identify and test ESIP member data sets to be recognized as trusted data sources for agencies and organizations responding to disasters. http://tinyurl.com/ GA4Disasters Dan Mandl – daniel.j.mandl@nasa.gov@nasa.gov NASA Goddard Space Flight Center Patrice Cappelaere – pat@cappelaere.com Vightel Corporation@ Kevin Dobbs – kevindobbs@ku.edukevindobbs@ku.edu Kansas Biological Survey Karen L. Moe – karen.moe@nasa.govkaren.moe@nasa.gov NASA Earth Science Technology Office Goddard Space Flight Center John D. Evans – john.evans@gst.com Global Science & Technology, Inc.john.evans@gst.com Stuart W. Frye – stuart.w.frye@nasa.gov Stinger Ghaffarian Technologies, Inc. Background Image Source: Iceland Holuhraun Volcano taken on 21 Oct. 2014 by NASA’s EO-1 satellite managed by GSFC. Image processing by I. Jónsdóttir, Univ. of Iceland Background Image Source: Iceland Holuhraun Volcano taken on 21 Oct. 2014 by NASA’s EO-1 satellite managed by GSFC. Image processing by I. Jónsdóttir, Univ. of Iceland Information Content Terminology => Taxonomy => Ontology => Tools Transforming Earth Observation Data Into Actionable Products UAH example of data albums involving severe storm users to identify, categorize & package storm event datasets and products Authoritative data securely shared Products Generated California Earthquake Clearinghouse JPL example of decision makers involvement via Interchange workshops on products & availability Understand and Leverage Relationships Best Practices re: User Needs, Tasks, Experience, Environment, Content and Context Landsat 8 example: Haiti reference water mask (76MB TIF) Vectorization: Surface water auto trace conversion via: - GeoJSON (10.6MB) - TopoJSON (3.5MB) - Simplify Lines Algorithm & compress (350KB) NASA Goddard SensorWeb example of low bandwidth access by users in the field Cross platform and cross product collaboration enabling framework Image Courtesy: Rafael Ameller


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