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Introduction to Information Quality Read chapter Read first chapter

2016 | OriginalPaper | Chapter

14. Quality of Web Data and Quality of Big Data: Open Problems

Authors : Monica Scannapieco, Laure Berti

Published in: Data and Information Quality

Publisher: Springer International Publishing

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Abstract

In this chapter we discuss some open issues related to two typologies of information sources that nowadays are particularly significant, namely, Web data and Big Data.

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Footnotes
Literature
19.
Amann B, Constantin C, Caron C, Giroux P (2013) Weblab prov: computing fine-grained provenance links for xml artifacts. In: EDBT/ICDT Workshops, pp 298–306
22.
Anand MK, Bowers S, Ludscher B (2010) Techniques for efficiently querying scientific workflow provenance graphs. In: International Conference on Extending Database Technology (EDBT), pp 287–298
35.
Barcaroli G, Nurra A, Scarno M, Summa D (2014) Use of web scraping and text mining techniques in the istat survey on information and communication technology in enterprises. In: Proceedings of Quality Conference 2014 (Q2014), Wien
53.
Bender C, Orszag S (1999) Advanced Mathematical Methods for Scientists and Engineers: Asymptotic Methods and Perturbation Theory. Springer, New YorkCrossRefMATH
78.
Bizer C (2007) Quality-driven information filtering in the context of web-based information systems. PhD thesis, Freie Universität Berlin
84.
Bonatti PA, Hogan A, Polleres A, Sauro L (2011) Robust and scalable linked data reasoning incorporating provenance and trust annotations. Journal of Web Semantics 9(2):165–201CrossRef
87.
Bowers S, McPhillips T, Ludscher B (2012) Declarative rules for inferring fine-grained data provenance from scientific workflow execution traces. In: International Provenance and Annotation Workshop (IPAW), pp 1–15
88.
89.
Boyd D, Crawford K (2012) Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Information, Communication, & Society 15(5)
98.
Buneman P, Khanna S, Tan WC (2001) Why and where: a characterization of data provenance. In: Proceedings of the 8th International Conference on Database Theory (ICDT)
99.
Burke J, Estrin D, Hansen M, Parker A, Ramanathan N, Reddy S, Srivastava MB (2006) Participatory sensing. In: Proceedings of the Workshop on World-Sensor-Web (WSW) at ACM Conference on Embedded Networked Sensor Systems (SenSys 2006), Boulder, pp 417–418
112.
Carroll J (2003) Signing rdf graphs. Technical report, HPL-2003-142, HP Labs
125.
Chen H, Ku W, Wang H, Sun M (2010) Leveraging spatio-temporal redundancy for rfid data cleansing. In: Proceedings of SIGMOD 2010, Indianapolis, pp 51–62
128.
Cheney J, Chiticariu L, Tan W (2007) Provenance in Databases: Why, How, and Where. Foundations and Trends in Databases 1:379–474CrossRef
132.
Chirigati F, Freire J (2012) Towards integrating workflow and database provenance. In: 4th International Provenance and Annotation Workshop (IPAW 2012), pp 11–23
158.
Cui Y, Widom J, Wiener JL (2000) Tracing the Lineage of View Data in a Warehousing Environment. ACM Transactions on Database Systems 25(2):179–227CrossRef
174.
Dempster A, Laird N, Rubin D (1977) Maximum likelihood from incomplete data via the EM algorithm. Journal of Royal Statistical Society 39:1–38MathSciNetMATH
176.
Dividino R, Sizov S, Staab S, Schueler B (2009) Querying for provenance, trust, uncertainty and other meta knowledge in RDF. Web Semantics: Science, Services and Agents on the World Wide Web 7:204–219CrossRef
177.
181.
Dong XL, Berti-Equille L, Srivastava D (2009) Truth discovery and copying detection in a dynamic world. PVLDB 2(1):562–573
185.
Duda R, Hart P, Stork D (2000) Pattern Classification. Wiley, New YorkMATH
229.
Fellegi IP, Sunter AB (1969) A theory for record linkage. Journal of the American Statistical Association 64
238.
252.
Galland A, Abiteboul S, Marian A, Senellart P (2010) Corroborating information from disagreeing views. In: WSDM, pp 131–140
253.
Gallegos I, Gates A, Tweedie C (2010) Dapros: a data property specification tool to capture scientific sensor data properties. In: Proceedings of ER Workshops. Vancouver, BC, pp 232–241
254.
Gamble M, Goble C (2011) Quality, trust, and utility of scientific data on the web: towards a joint model. In: ACM WebScience, pp 1–8
263.
Gil Y, Artz D (2007) Towards content trust of web resources. Web Semantics 5(4):227–239CrossRef
264.
Gil Y, Ratnakar V (2002) Trusting information sources one citizen at a time. In: ISWC. Springer, New York, pp 162–176MATH
267.
269.
Golbeck J (2004) Inferring reputation on the semantic web. In: WWW
298.
Hartig O (2008) Trustworthiness of data on the web. In: STI Berlin and CSW PhD Workshop, Berlin
299.
Hartig O (2009) Provenance information in the web of data. In: Proceedings of the Linked Data on the Web (LDOW’09), Workshop of the World Wide Web Conference (WWW)
304.
Heath T, Bizer C (2011) Linked Data: Evolving the Web into a Global Data Space. Morgan & Claypool
315.
Hopkins D, King G (2010) A method of automated nonparametric content analysis for social science. American Journal of Political Science 54(1):229–247CrossRef
336.
Jacobi I, Kagal L, Khandelwal A (2011) Rule-based trust assessment on the semantic web. In: International Conference on Rule-Based Reasoning, Programming, and Applications Series, pp 227–241
338.
James G, Witten D, Hastie T, Tibshirani R (2013) An Introduction to Statistical Learning with Applications in R. Springer Texts in Statistics. Springer, New YorkCrossRefMATH
346.
Jeffery S, Alonso M Gand Franklin, Hong W, Widom J (2005) A Pipelined Framework for Online Cleaning of Sensor Data Streams. Technical report, Computer Science Division (EECS), University of California, uCB/CSD-5-1413
347.
Jeffery S, Garofalakis M, Franklin M (2006) Adaptive cleansing for rfid data streams. In: Proceedings of Very Large Database Conference (VLDB 2006), Seoul, 2006, pp 163–174
371.
Klein A, Lehner W (2009) Representing data quality in sensor data streaming environments. Journal of Data and Information Quality 1(2)
386.
Lantz B (2013) Machine Learning with R. Packt Publishing Ltd
401.
Li X, Dong XL, Lyons K, Srivastava D (1999) Truth finding on the deep web: is the problem solved? In: PVLDB
407.
423.
Madhavan J, Ko D, Kot L, Ganapathy V, Rasmussen A, Halevy AY (2008) Google’s deep web crawl. PVLDB 1(2):1241–1252
427.
Manzoor A, Truong H, S D (2008) On the evaluation of quality of context. In: European Conference on Smart Sensing & Context (EuroSSC), Zurich, pp 140–153
435.
436.
Mendes P, Mühleisen H, Bizer C (2012) Sieve: linked data quality assessment and fusion. In: LWDMCrossRef
460.
496.
Pei L, Dong XL, Maurino M, Srivastava D (2011) Linking temporal records. Frontiers of Computer ScienceMATH
497.
Perkowitz M, Etzioni O (2000) Adaptive web-sites. Communication of the ACM 43(8)
506.
Planet B (2000) The deep web: Surfacing hidden value. The Journal of Electronic Publishing
517.
Rao J, Doraiswamy S, Thakkar H, Colby L (2006) A deferred cleansing method for rfid data analytics. In: Proceedings of Very Large Database Conference (VLDB 2006), Seoul, pp 175–186
543.
Salamone S, Scannapieco, Scarno M (2014) Web scraping and web mining: new tools for official statistics. In: Proceedings of Societa Italiana di Statistica (SIS 2014), Cagliari, Sardegna
551.
Scannapieco M, Virgillito A, Zardetto D (2013) Placing big data in official statistics: a big challenge? In: Proceedings of 2013 New Techniques and Tools for Statistics (NTTS) Conference, Brussels
562.
Sha K, Shi W (2008) Consistency-driven data quality management of networked sensor systems. Journal of Parallel and Distributed Computing 68(9):1207–1221CrossRef
569.
Shekarpour S, Katebi S (2010) Modeling and evaluation of trust with an extension in semantic web. Web Semantics: Science, Services and Agents on the World Wide Web 8(1):26–36CrossRef
599.
Talukdar PP, Jacob M, Mehmood MS, Crammer K, Ives ZG, Pereira F, Guha S (2008) Learning to create data-integrating queries. PVLDB 1(1):785–796
600.
Talukdar PP, Ives ZG, Pereira F (2010) Automatically incorporating new sources in keyword search-based data integration. In: SIGMOD Conference 2010, pp 387–398
602.
Tan WC (2007) Provenance in databases: past, current, and future. IEEE Data Engineering Bulletin 30(4):3–12
607.
Theoharis Y, Fundulaki I, Karvounarakis G, Christophides V (2011) On provenance of queries on semantic web data. IEEE Internet Computing 15(1):31–39CrossRef
609.
Thirunarayan K, Anantharam P, Henson C, Sheth A (2013) Comparative trust management with applications: Bayesian approaches emphasis. Future Generation Computer Systems
616.
634.
Vydiswaran VGV, Zhai C, Roth D (2011) Content-driven trust propagation framework. In: KDD, pp 974–982
635.
636.
679.
Wu W, Yu CT, Doan A, Meng W (2004) An interactive clustering-based approach to integrating source query interfaces on the deep web. In: SIGMOD Conference, pp 95–106
688.
Yin X, Han J (2007) Truth discovery with multiple conflicting information providers on the web. In: Proceedings of the 2007 ACM SIGKDD International Conference Knowledge Discovery in Databases (KDD’07)
690.
Zardetto D, Scannapieco M, Catarci T (2010) Effective automated object matching. In: Proceedings of the International Conference on Data Engineering (ICDE 2010), pp 757–768
691.
Zardetto D, Valentino L, Scannapieco M (2011) MAERLIN: new record linkage methods at work. In: Proceedings of the 6th International Conference on New Techniques and Technologies for Statistics (NTTS 2011)
694.
Zhao B, Rubinstein BIP, Gemmell J, Han J (2012) A Bayesian approach to discovering truth from conflicting sources for data integration. PVLDB 5(6):550–561
Metadata
Title
Quality of Web Data and Quality of Big Data: Open Problems
Authors
Monica Scannapieco
Laure Berti
Copyright Year
2016
Book
Data and Information Quality

Print ISBN: 978-3-319-24104-3

Electronic ISBN: 978-3-319-24106-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-24106-7_14

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