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ACM Journal of

Data and Information Quality (JDIQ)

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Latest Articles

On the Effects of Low-Quality Training Data on Information Extraction from Clinical Reports

In the last five years there has been a flurry of work on information extraction from clinical documents, that is, on algorithms capable of... (more)

Challenges of Open Data Quality

Challenge Paper

NEWS

March, 2017 -- Call for Papers: Special issue on Reproducibility in Information Retrieval Extended Submission deadline: October 6, 2017 

Feb. 2017 -- Call for Papers: 
Special Issue on Improving the Veracity and Value of Big Data 
Extended Submission deadline: April  1st, 2017

Jan. 2016 -- New Book Announcement
Carlo Batini and Monica Scannapieco have a new book:

Data and Information Quality: Dimensions, Principles and Techniques 

Springer Series: Data-Centric Systems and Applications, soon available from the Springer shop

The Springer flyer is available here


Experience and Challenge papers:  JDIQ now accepts two new types of papers. Experience papers describe real-world applications, datasets and other experiences in handling poor quality data. Challenges papers briefly describe a novel problem or challenge for the IQ community. See Author Guidelines for details.

Forthcoming Articles

Foreword from the New JDIQ Editor-in-Chief

Information Quality Challenges in Shared Healthcare Decision Making

Healthcare is evolving towards patient-centered care, and Shared Decision Making (SDM) holds great promise to improve health, reduce costs, and better align care with patients values. Information quality is a key aspect to empowering patients to make informed decisions. However, the progress on shared decision making is impeded by several unresolved information quality challenges. In this paper we propose three key challenges we believe need to be addressed to better facilitate SDM, including consistency and reconciliation, optimizing timeliness and accuracy tradeoff, and integrating decision aids. We call on the information quality community to begin addressing the challenges above to support the on-going transition of healthcare to SDM.

Cluster-based Quality-Aware Adaptive Data Compression for Streaming Data

Wireless sensor networks are widely applied in data collection applications. Energy efciency is one of the most important design goals. In this paper, we propose QAAC, Quality-Assured Adaptive data Compression, to reduce the amount of data communication so that to save energy. QAAC rst builds clusters from dataset using an adaptive clustering algorithm; then a code for each cluster is generated and stored in a Huffman encoding tree, which is used to encode the original dataset in an encoding algorithm with improvement approach. After the encoded data, the Huffman encoding tree and parameters used in the improvement algorithm have been received at the sink, a decompression algorithm is used to retrieve the approximation of the original dataset. The performance evaluation shows that QAAC is efcient and achieves much higher compression ratio than compared lossy and lossless compression algorithms and much less information loss than compared lossy compression algorithms.

Data Quality Challenges in Social Spam Research

Spam on Online Social Networks (OSNs) has received a booming interest in the last few years. Following the rise of these platforms and their establishment as a ubiquitous part of the online existence, spammers have found in them an opportunity to make a lucrative business. A major part of the literature that aims at detecting spammers on OSNs uses the supervised learning model as the building schema of their contributions. This model assumes that it is possible to classify entities based on their statistical characteristics. A vital condition for the successful implementation of this model is to ensure that data is collected and labeled in a clean, accurate and non-biased way, resulting in high-quality datasets. In this paper, we discuss the different steps of the supervised classification methodology applied to social spam detection. This includes data collection, labeling, transformation, and sharing. From this, various issues arise in relation to collection bias, inaccurate and irreproducible labeling, obscure provenance of adjunct datasets (such as blacklists and spam dictionaries), imprecise description of features extraction and data transformation, and finally, complete or partial unavailability of raw and final datasets used to build statistical decision models.

Comparative analysis of sequence clustering methods for de-duplication of biological databases

The massive volumes of data in biological sequence databases provide a remarkable resource for large-scale biological studies. However the underlying data quality of these resources is a critical concern. A particular is duplication, in which multiple records have similar sequences, creating a high level of redundancy that impacts database storage, curation, and search. Biological database de-duplication has two direct applications: for database curation, where detected duplicates are removed to improve curation efficiency; and for database search, where detected duplicate sequences may be flagged but remain available to support analysis. Clustering methods have been widely applied to biological sequences for database de-duplication. Given high volumes of data, exhaustive all-by-all pairwise comparison of sequences cannot scale, and thus heuristics have been used, in particular use of simple similarity thresholds. This heuristic introduces a trade-off between efficiency and accuracy that we explore in this paper: if the similarity threshold is very high, the methods are accurate but slow; if the similarity threshold is too low, the methods are fast but inaccurate. We study the two best-known clustering tools for sequence database de-duplication, CD-HIT and UCLUST. Our contributions include: a detailed assessment of the redundancy remaining after de-duplication; application of standard clustering evaluation metrics to quantify the cohesion and separation of the clusters generated by each method; and a biological case study that assesses intra-cluster function annotation consistency, to demonstrate the impact of these factors in practical application of the sequence clustering methods. The results show that the trade-off between efficiency and accuracy becomes acute when low threshold values are used and when cluster sizes are large. The evaluation leads to practical recommendations for users for more effective use of the sequence clustering tools for de-duplication.

Editor in Chief (January 2014 - May 2017) Farewell Report

Validating data quality actions in scoring processes

Data Quality is gaining momentum among organizations from when they realized that poor data quality might cause failures and/or inefficiencies, thus compromising business processes and application results. However, enterprises often adopt data quality assessment and improvement methods based on practical and empirical approaches, without conducting a rigorous analysis of the data quality issues and the outcome of the enacted data quality improvement practices. In particular, data quality management, and especially the identification of the data quality dimensions to be monitored and improved is up to knowledge-workers on the basis of their skills and experience. Control methods are therefore designed on the basis of expected and evident quality problems and thus they may not be effective in dealing with unknown and/or unexpected problems. This paper aims to provide a methodology, based on fault injection, for validating the data quality actions used by organizations. We show how it is possible to check if the adopted techniques properly monitor the real issues that may damage business processes. At this stage we focus on scoring processes, i.e., processes in which the output represents the evaluation or ranking of a specific object. We show the effectiveness of our proposal by means of a case study in the financial risk management area.

Bibliometrics

Publication Years 2009-2017
Publication Count 126
Citation Count 220
Available for Download 126
Downloads (6 weeks) 1201
Downloads (12 Months) 12601
Downloads (cumulative) 80703
Average downloads per article 641
Average citations per article 2
First Name Last Name Award
Peter Aiken ACM Senior Member (2011)
Mikhail Atallah ACM Fellows (2006)
Ahmed Elmagarmid ACM Fellows (2012)
ACM Distinguished Member (2009)
Wenfei Fan ACM Fellows (2012)
Matthias Jarke ACM Fellows (2013)
Daniel S Katz ACM Senior Member (2011)
Beth A. Plale ACM Senior Member (2006)

First Name Last Name Paper Counts
Yang Lee 4
Peter Christen 3
John Talburt 3
G Shankaranarayanan 3
Stuart Madnick 3
Nan Tang 3
Ross Gayler 2
Dinusha Vatsalan 2
Wolfgang Lehner 2
Daisyzhe Wang 2
Ali Sunyaev 2
Vassilios Verykios 2
Wenfei Fan 2
Peter Edwards 2
Felix Naumann 2
Roman Lukyanenko 2
Roger Blake 2
Arnon Rosenthal 2
Sherali Zeadally 2
Eitel LauríA 2
Carolyn Matheus 2
Xiaobai Li 2
Christan Grant 2
Mario Mezzanzanica 1
Roberto Boselli 1
Luvai Motiwalla 1
Sandra Geisler 1
Daniel Katz 1
Douglas Hodson 1
Dov Biran 1
Edward Anderson 1
Pierpaolo Vittorini 1
Karthikeyan Ramamurthy 1
Ralf Tönjes 1
Laurent Lecornu 1
Shelly Sachdeva 1
Stuart Madnick 1
Monica Tremblay 1
Debra Vandermeer 1
Foster Provost 1
Nicola Ferro 1
Christian Becker 1
Chintan Amrit 1
Sharad Mehrotra 1
Sandra Sampaio 1
Sören Auer 1
Christoph Lange 1
Dustin Lange 1
Therese Williams 1
Jianyong Wang 1
Chris Baillie 1
Beth Plale 1
John Krogstie 1
Banda Ramadan 1
John O’Donoghue 1
Wenjun Li 1
Davide Ceolin 1
Khoi Tran 1
Lan Cao 1
Payam Barnaghi 1
Jean Caillec 1
Arputharaj Kannan 1
Anupkumar Sen 1
Rashid Ansari 1
Fahima Nader 1
Philip Woodall 1
Shuai Ma 1
Nigel Martin 1
Axel Polleres 1
Venkata Meduri 1
Suzanne Embury 1
Hubert Österle 1
Erhard Rahm 1
Lizhu Zhou 1
Jeffrey Vaughan 1
Melanie Herschel 1
Huizhi Liang 1
Paolo Coletti 1
Mirko Cesarini 1
Hongjiang Xu 1
Vincenzo Maltese 1
Fred Morstatter 1
Paul Groth 1
Valentina Maccatrozzo 1
Mohamed Yakout 1
A Borthick 1
Sara Tonelli 1
Kush Varshney 1
Rahul Basole 1
Jimeng Sun 1
Dmitry Chornyi 1
Danilo Montesi 1
Omar Alonso 1
Ashfaq Khokhar 1
Alan Labouseur 1
Alexandra Poulovassilis 1
Yuheng Hu 1
Yi Chen 1
Robert Meusel 1
Maurice Van Keulen 1
Irit Askira Gelman 1
Stephen Chong 1
Edoardo Pignotti 1
Fabiano Tarlao 1
Eric Medvet 1
John Herbert 1
Juan Augusto 1
Maurice Mulvenna 1
Paul Mccullagh 1
Fabio Mercorio 1
Fei Chiang 1
Siddharth Sitaramachandran 1
J Jha 1
Laure Berti-Équille 1
Sven Weber 1
Richard Briotta 1
Johann Freytag 1
María Bermúdez-Edo 1
Maria Alvarez 1
Panagiotis Ipeirotis 1
Justin St-Maurice 1
Milan Markovic 1
Wenyuan Yu 1
Jürgen Umbrich 1
Fabian Panse 1
Xiaoping Liu 1
Fumiko Kobayashi 1
Paolo Missier 1
Kristin Weber 1
Paul Glowalla 1
Wenyuan Yu 1
Xu Pu 1
Benjamin Ngugi 1
Beverly Kahn 1
Fausto Giunchiglia 1
Christoph Quix 1
Matthias Jarke 1
Wan Fokkink 1
Jeffrey Fisher 1
Adriane Chapman 1
Jeremy Millar 1
Heiko Müller 1
Hilko Donker 1
Terry Clark 1
H Nehemiah 1
Steven Brown 1
Matthew Jensen 1
Jay Nunamaker, 1
Adir Even 1
Rachid Chalal 1
Fons Wijnhoven 1
Sushovan De 1
Dominique Ritze 1
Heiko Paulheim 1
Dezhao Song 1
Rabia Nuray-Turan 1
Dmitri Kalashnikov 1
Yinle Zhou 1
Jeremy Debattista 1
Tobias Vogel 1
Arvid Heise 1
Uwe Draisbach 1
Youwei Cheah 1
Daniel Dalip 1
Pável Calado 1
Olivier Curé 1
Claire Collins 1
Ioannis Anagnostopoulos 1
Patricia Franklin 1
Huan Liu 1
Willem Van Hage 1
Len Seligman 1
Gilbert Peterson 1
Hongwei Zhu 1
Michael Zack 1
Nitin Joglekar 1
Ulf Leser 1
Irit Gelman 1
Mikhail Atallah 1
Yanjuan Yang 1
Paul Bowen 1
Peter Aiken 1
Robert Ulbricht 1
Martin Hahmann 1
Dennis Wei 1
Aleksandra Mojsilović 1
Ion Todoran 1
Ali Khenchaf 1
Subhash Bhalla 1
D Elizabeth 1
Trent Rosenbloom 1
Shawn Hardenbrook 1
Kaushik Dutta 1
Jeffrey Parsons 1
Valerie Sessions 1
Kresimir Duretec 1
Leena Al-Hussaini 1
Pim Dietz 1
Eric Nelson 1
Manoranjan Dash 1
M Kaiser 1
Floris Geerts 1
Thomas Redman 1
David Becker 1
Xiaoming Fan 1
Giannis Haralabopoulos 1
Kyle Niemeyer 1
Arfon Smith 1
Archana Nottamkandath 1
Darryl Ahner 1
Hongwei Zhu 1
Cihan Varol 1
Coşkun Bayrak 1
David Robb 1
Claudio Hartmann 1
Rosella Gennari 1
Mark Braunstein 1
Marta Zárraga-Rodríguez 1
Peter Elkin 1
C Raj 1
Hema Meda 1
Amitava Bagchi 1
Matteo Magnani 1
Craig Fisher 1
Sufyan Ababneh 1
Jiannan Wang 1
Jianing Wang 1
Sebastian Neumaier 1
Norbert Ritter 1
R Greenwood 1
Ayush Singhania 1
George Moustakides 1
Hongwei Zhu 1
Bernd Heinrich 1
Mathias Klier 1
Bing Lv 1
Paul Mangiameli 1
Dirk Ahlers 1
Marcos Gonçalves 1
Alberto Bartoli 1
James McNaull 1
Kelly Janssens 1
Judith Gelernter 1
Mouhamadoulamine Ba 1
Ciro D'Urso 1
Hua Zheng 1
Ahmed Elmagarmid 1
Michael Mannino 1
Fiona Rohde 1
Kewei Sha 1
Elliot Fielstein 1
Theodore Speroff 1
Yang Lee 1
Judee Burgoon 1
Josh Attenberg 1
Marco Valtorta 1
Sean Goldberg 1
Andreas Rauber 1
Sabrina Abdellaoui 1
Catherine Burns 1
Subbarao Kambhampati 1
Jeff Heflin 1
Alun Preece 1
Anja Klein 1
Boris Otto 1
Richard Wang 1
Alan March 1
Marilyn Tremaine 1
Christian Skalka 1
Maurizio Murgia 1
Marco Cristo 1
Andrea Lorenzo 1

Affiliation Paper Counts
University of Padua 1
University of Illinois at Urbana-Champaign 1
Federal University of Amazonas 1
Florida State University 1
Virginia Commonwealth University 1
Vanderbilt University 1
Instituto Superior Tecnico 1
Google Inc. 1
University of Leipzig 1
Hospital Universitario Austral 1
Harvard University 1
University of Colorado at Denver 1
Oklahoma City University 1
University of Rhode Island 1
State University of New York at Albany 1
Georgia State University 1
University of Antwerp 1
University of Texas at Austin 1
Oregon State University 1
Beihang University 1
University of Massachusetts System 1
Indian Institute of Science 1
Elsevier 1
University of Augsburg 1
Vienna University of Technology 1
University of South Carolina 1
Simon Fraser University 1
Memorial University of Newfoundland 1
Boston University 1
Technical University of Munich 1
Butler University 1
New Jersey Institute of Technology 1
National Institute of Standards and Technology 1
Cardiff University 1
Sam Houston State University 1
University College Cork 1
Microsoft Corporation 1
Ben-Gurion University of the Negev 1
Charleston Southern University 1
Commonwealth Scientific and Industrial Research Organization 1
Rutgers, The State University of New Jersey 1
University of Cambridge 1
University of Patras 1
Hellenic Open University 1
Universite Paris-Est 1
Lehigh University 2
Humboldt University of Berlin 2
Fraunhofer Institute for Applied Information Technology 2
Nanyang Technological University 2
Old Dominion University 2
Suffolk University 2
Free University of Bozen-Bolzano 2
University of Innsbruck 2
University of Arizona 2
Norwegian University of Science and Technology 2
University of Waterloo 2
University of Kentucky 2
University of Trento 2
RWTH Aachen University 2
University of Toronto 2
University of Surrey 2
Indiana University 2
New York University 2
Massachusetts Institute of Technology 2
University of Massachusetts Boston 2
University of Bologna 2
University of Hamburg 2
Federal University of Minas Gerais 2
University of Oklahoma 2
University of Queensland 2
University of Aizu 2
McMaster University 2
Universidad de Navarra 2
Indian Institute of Management Calcutta 2
Vienna University of Economics and Business Administration 3
University of Massachusetts Medical School 3
University of Mannheim 3
University of California, Irvine 3
University of Bonn 3
Birkbeck University of London 3
Purdue University 3
Telecom Bretagne 3
Georgia Institute of Technology 3
University of Cologne 3
Babson College 3
University of Thessaly 3
University of St. Gallen 3
Northeastern University 3
Ecole nationale superieure d'Informatique 3
University of Manchester 4
Vrije Universiteit Amsterdam 4
University of Milan - Bicocca 4
University of Florida 4
IBM Thomas J. Watson Research Center 4
Technical University of Dresden 4
University of Trieste 4
United States Air Force Institute of Technology 4
University of Twente 4
University of Ulster 4
Anna University 4
United States Department of Veterans Affairs 4
University of Edinburgh 4
University of Illinois at Chicago 4
Qatar Computing Research institute 4
Florida International University 5
University of Massachusetts Lowell 5
Marist College 5
Arizona State University 5
MITRE Corporation 5
University of Aberdeen 5
Tsinghua University 5
Hasso-Plattner-Institut fur Softwaresystemtechnik GmbH 6
University of Arkansas at Little Rock 8
Australian National University 9
 
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