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Data Profiling
Data profiling refers to the activity of collecting data about data, {i.e.}, metadata. Most IT professionals and researchers who work with data have engaged in data profiling, at least informally, to understand and explore an unfamiliar dataset or to determine whether a new dataset is appropriate for a particular task at hand. Data profiling results are also important in a variety of other situations, including query optimization, data integration, and data cleaning. Simple metadata are statistics, such as the number of rows and columns, schema and datatype information, the number of distinct values, statistical value distributions, and the number of null or empty values in each column. More...
Scalable Processing of Spatial-Keyword Queries
Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial-keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts ...
Community Search over Big Graphs
Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention, from small, simple, and static graphs to big, evolving, attributed, and location-based graphs. In this book, we first review the basic concepts of networks, communities, and various kinds of dense subgraph models. We then survey the state of the art in community search techniques on various kinds of networks across different application areas. Specifically, we discuss cohesive community search, attributed community s...
Fault-Tolerant Distributed Transactions on Blockchain
Since the introduction of Bitcoin—the first widespread application driven by blockchain—the interest of the public and private sectors in blockchain has skyrocketed. In recent years, blockchain-based fabrics have been used to address challenges in diverse fields such as trade, food production, property rights, identity-management, aid delivery, health care, and fraud prevention. This widespread interest follows from fundamental concepts on which blockchains are built that together embed the notion of trust, upon which blockchains are built. 1. Blockchains provide data transparancy. Data in a blockchain is stored in the form of a ledger, which contains an ordered history of all the transa...
Database Systems for Advanced Applications
This two volume set LNCS 9049 and LNCS 9050 constitutes the refereed proceedings of the 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, held in Hanoi, Vietnam, in April 2015. The 63 full papers presented were carefully reviewed and selected from a total of 287 submissions. The papers cover the following topics: data mining; data streams and time series; database storage and index; spatio-temporal data; modern computing platform; social networks; information integration and data quality; information retrieval and summarization; security and privacy; outlier and imbalanced data analysis; probabilistic and uncertain data; query processing.
The Four Generations of Entity Resolution
Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency. The initial ER methods primarily target Veracity in the context of structured (relational) data that are described by a schema of well-known quality and meaning. To achieve high effectiveness, they leverage schema, expert, and/or external knowledge. Part of these methods are extended to address Volume, processing large datasets through multi-core or massive parallelization approaches, such as the MapReduce paradigm. However, these early schema-based approaches are inapplicable to Web Data, which abound in voluminous, noi...
Data-Intensive Workflow Management
Workflows may be defined as abstractions used to model the coherent flow of activities in the context of an in silico scientific experiment. They are employed in many domains of science such as bioinformatics, astronomy, and engineering. Such workflows usually present a considerable number of activities and activations (i.e., tasks associated with activities) and may need a long time for execution. Due to the continuous need to store and process data efficiently (making them data-intensive workflows), high-performance computing environments allied to parallelization techniques are used to run these workflows. At the beginning of the 2010s, cloud technologies emerged as a promising environmen...
New Trends in Databases and Information Systems
This book constitutes the thoroughly refereed short papers, workshops and doctoral consortium papers of the 22th European Conference on Advances in Databases and Information Systems, ADBIS 2018, held in Budapest, Hungary, in September 2018. The 20 full and the 4 short workshop papers as well as the 3 doctoral consortium papers were carefully reviewed and selected from 54 submissions to the workshops and 6 submissions to the doctoral consortium. Furthermore, there are 10 short papers included, which were accepted for the main conference. The papers are organized according to the 6 workshops and the doctoral consortium: ADBIS 2018 short papers; First Workshop on Advances on Big Data Management...
Internet of Things—Applications and Future
This book is a collection of the best research papers presented at the First World Conference on Internet of Things: Applications & Future (ITAF 2019), Sponsored by GR Foundation and French University in Egypt, held at Triumph Luxury Hotel, Cairo, Egypt, on 14–15 October 2019. It includes innovative works from leading researchers, innovators, business executives, and industry professionals that cover the latest advances in and applications for commercial and industrial end users across sectors within the emerging Internet of Things ecosphere. It addresses both current and emerging topics related to the Internet of Things such as big data research, new services and analytics, Internet of Things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies, and open and cloud technologies.
Transaction Processing on Modern Hardware
The last decade has brought groundbreaking developments in transaction processing. This resurgence of an otherwise mature research area has spurred from the diminishing cost per GB of DRAM that allows many transaction processing workloads to be entirely memory-resident. This shift demanded a pause to fundamentally rethink the architecture of database systems. The data storage lexicon has now expanded beyond spinning disks and RAID levels to include the cache hierarchy, memory consistency models, cache coherence and write invalidation costs, NUMA regions, and coherence domains. New memory technologies promise fast non-volatile storage and expose unchartered trade-offs for transactional durabi...
