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Journal of Data and Information Quality (JDIQ) - Special Issue on Improving the Veracity and Value of Big Data, Volume 9 Issue 3, March 2018

Section: Special Issue on Improving the Veracity and Value of Big Data

Editorial: Special Issue on Improving the Veracity and Value of Big Data
Floris Geerts, Paolo Missier, Norman Paton
Article No.: 13
DOI: 10.1145/3174791

Ontological Multidimensional Data Models and Contextual Data Quality
Leopoldo Bertossi, Mostafa Milani
Article No.: 14
DOI: 10.1145/3148239

Data quality assessment and data cleaning are context-dependent activities. Motivated by this observation, we propose the Ontological Multidimensional Data Model (OMD model), which can be used to model and represent contexts as logic-based...

Scalable Methods for Measuring the Connectivity and Quality of Large Numbers of Linked Datasets
Michalis Mountantonakis, Yannis Tzitzikas
Article No.: 15
DOI: 10.1145/3165713

Although the ultimate objective of Linked Data is linking and integration, it is not currently evident how connected the current Linked Open Data (LOD) cloud is. In this article, we focus on methods, supported by special indexes and...

Toward Veracity Assessment in RDF Knowledge Bases: An Exploratory Analysis
Diego Esteves, Anisa Rula, Aniketh Janardhan Reddy, Jens Lehmann
Article No.: 16
DOI: 10.1145/3177873

Among different characteristics of knowledge bases, data quality is one of the most relevant to maximize the benefits of the provided information. Knowledge base quality assessment poses a number of big data challenges such as high volume,...

Comparative Analysis of Sequence Clustering Methods for Deduplication of Biological Databases
Qingyu Chen, Yu Wan, Xiuzhen Zhang, Yang Lei, Justin Zobel, Karin Verspoor
Article No.: 17
DOI: 10.1145/3131611

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 challenge is duplication, in...