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"In each of the phases of a Big Data analysis process, data quality (DQ) plays a key role. Given the particular characteristics of the data at hand, the traditional DQ methods used for relational databases, based on qual...

In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets an...

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication too...

"In each of the phases of a Big Data analysis process, Data Quality (DQ) plays a key role. Given the particular characteristics of the data at hand, the traditional DQ methods, based on quality dimensions and metrics, mu...

"This article studies the analysis of moving object data collected by location-aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so-called semantic trajectories, which are s...

"There is a general belief that the quality of Twitter data streams is generally low and unpredictable, making, in some way, unreliable to take decisions based on such data. The work presented here addresses this problem...

"The amount of multidimensional data published on the semantic web (SW) is constantly increasing, due to initiatives such as Open Data and Open Government Data, among other ones. Models, languages, and tools, that allow ...

"The interest in mobility data analysis has grown dramatically with the wide availability of devices that track the position of moving objects. Mobility analysis can be applied, for example, to analyze traffic flows. To ...

Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a n...

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding ...

Data quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software deve...

A general inductive approach for analysis of qualitative evaluation data is described. The purposes for using an inductive approach are to (a) condense raw textual data into a brief, summary format; (b) establish clear l...

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to co...

OBJECTIVES: Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this,...

In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip system with the objective of improving upon currently used measures of gene expression. Our analyses ma...

The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submiss...

When making sampling distribution inferences about the parameter of the data, θ, it is appropriate to ignore the process that causes missing data if the missing data are ‘missing at random’ and the observed data are...

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visuali...

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research...

Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, ...

Preface.PART I: OVERVIEW AND BASIC APPROACHES.Introduction.Missing Data in Experiments.Complete-Case and Available-Case Analysis, Including Weighting Methods.Single Imputation Methods.Estimation of Imputation Uncertainty...

BACKGROUND: the analysis of microbial communities through dna sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, vis...

"There is a general belief that the quality of Twitter data streams is generally low and unpredictable, making, in some way, unreliable to take decisions based on such data. The work presented here addresses this problem...

Context. We present the second Gaia data release, Gaia DR2, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21. In...