Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Why and Where: A Characterization of Data Provenance
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Text joins in an RDBMS for web data integration
WWW '03 Proceedings of the 12th international conference on World Wide Web
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Update exchange with mappings and provenance
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
MCDB: a monte carlo approach to managing uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Designing games with a purpose
Communications of the ACM - Designing games with a purpose
The Active XML project: an overview
The VLDB Journal — The International Journal on Very Large Data Bases
On the expressiveness of implicit provenance in query and update languages
ACM Transactions on Database Systems (TODS)
Fast and Simple Relational Processing of Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Proceedings of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications
Improving search engines using human computation games
Proceedings of the 18th ACM conference on Information and knowledge management
Corroborating information from disagreeing views
Proceedings of the third ACM international conference on Web search and data mining
On probabilistic fixpoint and Markov chain query languages
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Human-assisted graph search: it's okay to ask questions
Proceedings of the VLDB Endowment
A rule-based language for web data management
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
CrowdDB: answering queries with crowdsourcing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Deriving probabilistic databases with inference ensembles
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
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Crowdsourcing is an emerging paradigm that harnesses a mass of users to perform various types of tasks. We focus in this tutorial on a particular form of crowdsourcing, namely crowd (or mob) datasourcing whose goal is to obtain, aggregate or process data. We overview crowd datasourcing solutions in various contexts, explain the need for a principled solution, describe advances towards achieving such a solution, and highlight remaining gaps.