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Presentation of the project OpenFridge in the Workshop on Big Data and Society, in IEEE International Conference on Big Data (IEEE Big Data 2013)  6-9 October 2013, Silicon Valley, CA, USA
 

Presentation of the project OpenFridge in the Workshop on Big Data and Society, in IEEE International Conference on Big Data (IEEE Big Data 2013) 6-9 October 2013, Silicon Valley, CA, USA

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Presentation of the project OpenFridge in the Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era Part of ...

Presentation of the project OpenFridge in the Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013) 6-9 October 2013, Silicon Valley, CA, USA

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    Presentation of the project OpenFridge in the Workshop on Big Data and Society, in IEEE International Conference on Big Data (IEEE Big Data 2013)  6-9 October 2013, Silicon Valley, CA, USA Presentation of the project OpenFridge in the Workshop on Big Data and Society, in IEEE International Conference on Big Data (IEEE Big Data 2013) 6-9 October 2013, Silicon Valley, CA, USA Presentation Transcript

    • OPEN FRIDGE: A PLATFORM FOR DATA ECONOMY FOR ENERGY EFFICIENCY DATA Dr. Dana Tomic, FTW The Telecommunication Research Center Vienna, Austria Dr. Anna Fensel, University of Innsbruck, Semantic Technology Institute (STI), Austria Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Smart Grid is a Showcase for Data Economy Smart Grid Operation Synchro Phasers Smart Buildings Smart Metering Smart Cities Prosumers Compliance Energy Markets Price Signals Renewables Parks Smart Appliances Electro Mobility Compliance Plant Automation Demand Response Business DSM Capacity Management Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Economy for Energy Efficiency Data (Knowledge)?  What is energy efficiency? – Using less energy to provide equivalent service. – A life-cycle characteristic of home appliances.  – – – – How energy efficiency is being assessed? By measuring and comparison. EE of Design: Efficiency labels awarded by verification institutes. EE of Use: Best practices, comparisons  How potential for increasing energy efficiency is being assessed? – By measuring/comparison  More context needed More info: http://www.atlete.eu, http://eetd.lbl.gov/ee/ee-1.html Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • A Value-chain for Energy Efficiency Data  Metering (Data) - A source of big data, two-way exchange Dynamic tariffs, distributed generation, demand management Granularity of measurements aggregated vs. appliance level Provides energy awareness context  Energy Awareness (Knowledge) - Awareness context vs. usage context Awareness at the energy service level needed. Smart-plugs for individual measurements Label is a decision support tool pointing to technological improvements in energy efficiency of appliances.  Efficiency Increasing Actions - Appliance replacement, more efficient use, technology improvements Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • OpenFridge : Opening and Processing Appliances Data for Energy Efficiency  Building an ecosystem around data Improved labeling Better decisions about replacement and use Home Users Labeling Institutions Energy Efficiency Data Improved technology and CRM Manufacturers  Developing a crowdsourcing platform for data collection  Exploring the concept of context-dependent energy efficiency  Combining big data and semantics for add-value services Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Crowdsourcing and Data Market in Action Community & Content Management SPARQL: Dataas-a-Service Business Intelligence Services Manufacturers Labeling Orgs. Semantic Knowledge Base Usage Profile Big Data Infrastructure Appliance Profile Measurements Profile Volume? Variety? Velocity? Veracity? Value? Analytics Appliance Profile Measurements Profile Measurements Recommendations & Visualizations Users Drupal Portal & Web Service Client Data Acquisition Web Service Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • From Context to Recommendations Appliance profile type, volume, producer, efficiency, year of production, stand-alone/built-in, facing south, location: kitchen / cellar, city, country, number of users Measurement profile cooling level (1,2,3,..), inside temperature, room temperature, level of filling, doors opening events, measurement duration Measurements power level (5s) timestamp Usage profile avg. consumption, cooling cycle, defrost cycle,… Comparisons, Recommendations & Analytics Services Compare different refrigerators, refrigerators of the same type, performance at different environmental conditions, set-points and loadings, impact of opening the door, of aging, of installation, … Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Platform Enablers  Hardware & service interfaces for data acquisition - Currently based on the existing commercial system with web-service interface  Big data & analytics for data processing - Anticipating large user base  Semantic technology for value-add services - Easy integration of external data, vocabularies and ontologies from the ecommerce and energy efficiency domain - Logic-based reasoning  Privacy and security protection of data - Data provenance and veracity  Community building and crowdsourcing - Incentives based on high-quality recommendations Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Challenges  Interfaces - Attractiveness and usability of User interfaces for data acquisition Instrumentation for appliances data acquisition Privacy of user and appliances data Accuracy of data  Big Data - Analytics on raw data: mappers/reducers feed semantic knowledgebase with model data  Semantic Layer - Ontology engineering External data integration Performance of the semantic knowledgebase Expressiveness of services via SPARQL queries for B2B/B2C portalbased analytics Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Summary and Outlook  Experiment in progress !  Our Goal: A platform for crowdsourcing of energy efficiency data and a community for propagation of energy efficiency social values  Exploring the concept of context-dependent energy efficiency: - Measurements in a broader context of different usage parameters within a community of users - Providing necessary explanations to motivate corresponding users’ actions towards improving the energy efficiency of services.  Integrating Big Data and semantic technology - Maintaining large volumes of raw data, analytics to transform raw data into the parameterized information - Developing appropriate ontologies to link parameterized energy efficiency information with the usage context information  Developing semantic-based delivery of add-value services - Querying and Reasoning  Focusing on refrigerators as they are the largest energy consuming home appliance; the same principles could be further extended Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA
    • Contact Dr. S. Dana Kathrin Tomic Senior Researcher | Networked Services FTW Forschungszentrum Telekommunikation Wien GmbH Donau-City-Straße 1/3 | A-1220 Vienna | Austria tomic@ftw.at | www.ftw.at/~tomic +43/1/5052830 -54 | fax -99 | +43/6769129023 Thank you for your attention! Questions? Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era, Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013), 6-9 October 2013, Silicon Valley, CA, USA