Open Data

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Crowd-Sourcing Approaches “For (m)any data integration problem, if you don’t involve human, then there is no hope.” AnHai Doan © Prof. Dr.-Ing. Wolfgang Lehner| Do-It-Yourself Analytics on Open Data 26
CrowdDB Company_Name Address Market_Cap Google Googleplex, Mnt. View CA $210Bn Intl. Business Machines Armonk, NY $200Bn Microsoft Redmond, WA $250Bn SELECT Market_Cap FROM Companies WHERE Company_Name=“IBM“ SELECT Market_Cap FROM Companies WHERE Company_Name=“Apple“ Result: 0 rows Problem: Entity Resolution Result: 0 rows Problem: Closed World Assumption Hard queries for computers, very easy for humans © Prof. Dr.-Ing. Wolfgang Lehner| Do-It-Yourself Analytics on Open Data 27
Page 1 and 2: Do-It-Yourself Analytics on Open Da
Page 3 and 4: Why Data Should be Open • Many sc
Page 5 and 6: Civic Applications based on Open Da
Page 7 and 8: Fluglärmkarte (taz.de) © Prof. Dr
Page 9 and 10: Gapminder (2) Vision: making sense
Page 11 and 12: Mapnificient for Dresden © Prof. D
Page 13 and 14: Open Civic Platform for Dresden (2)
Page 15 and 16: What we are doing at EDYRA http://w
Page 17 and 18: Open Data Survey Why we did it? •
Page 19 and 20: Related Work © Prof. Dr.-Ing. Wolf
Page 21 and 22: Data Integration © Prof. Dr.-Ing.
Page 23 and 24: Open Data Problems Meta data qualit
Page 25: Semi-automatic Schema Annotation Mo
Page 29 and 30: CrowdDB (2) Architecture © Prof. D
Page 31 and 32: CrowdDB (4) Example User Interfaces
Page 33 and 34: Games with a purpose Motivation •
Page 35 and 36: Data Exploitation © Prof. Dr.-Ing.
Page 37 and 38: Motivation - Keyword Search Queryin
Page 39 and 40: Research Dimensions Model • Data
Page 41 and 42: Vision: Do-It-Yourself Analytics
Page 43 and 44: Vision: Do-It-Yourself Analytics (3
Page 45 and 46: Vision: Do-It-Yourself Analytics (5
Page 47 and 48: Bachelorthemen Extraktion semantisc
Page 49 and 50: Bachelorthemen III Schema-Extraktio

Open Data

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