Dagstuhl Follow-Ups, Volume 5

Data Exchange, Integration, and Streams



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Publication Details

  • published at: 2013-10-18
  • Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
  • ISBN: 978-3-939897-61-3
  • DBLP: db/conf/dagstuhl/dfu5

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Document
Complete Volume
DFU, Volume 5, Data Exchange, Integration, and Streams, Complete Volume

Authors: Phokion G. Kolaitis, Maurizio Lenzerini, and Nicole Schweikardt


Abstract
DFU, Volume 5, Data Exchange, Information, and Streams, Complete Volume

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Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@Collection{DFU.Vol5.10452,
  title =	{{DFU, Volume 5, Data Exchange, Integration, and Streams, Complete Volume}},
  booktitle =	{Data Exchange, Integration, and Streams},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452},
  URN =		{urn:nbn:de:0030-drops-43032},
  doi =		{10.4230/DFU.Vol5.10452},
  annote =	{Keywords: Heterogeneous Databases, Systems, Database Applications, Nonnumerical Algorithms and Problems}
}
Document
Frontmatter, Table of Contents, Preface

Authors: Phokion G. Kolaitis, Maurizio Lenzerini, and Nicole Schweikardt


Abstract
Frontmatter, Table of Contents, Preface

Cite as

Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{kolaitis_et_al:DFU.Vol5.10452.i,
  author =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  title =	{{Frontmatter, Table of Contents, Preface}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{0:i--0:x},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.i},
  URN =		{urn:nbn:de:0030-drops-42875},
  doi =		{10.4230/DFU.Vol5.10452.i},
  annote =	{Keywords: Frontmatter, Table of Contents, Preface}
}
Document
The Chase Procedure and its Applications in Data Exchange

Authors: Adrian Onet


Abstract
The initial and basic role of the chase procedure was to test logical implication between sets of dependencies in order to determine equivalence of database instances known to satisfy a given set of dependencies and to determine query equivalence under database constrains. Recently the chase procedure has experienced a revival due to its application in data exchange. In this chapter we review the chase algorithm and its properties as well as its application in data exchange.

Cite as

Adrian Onet. The Chase Procedure and its Applications in Data Exchange. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 1-37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{onet:DFU.Vol5.10452.1,
  author =	{Onet, Adrian},
  title =	{{The Chase Procedure and its Applications in Data Exchange}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{1--37},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.1},
  URN =		{urn:nbn:de:0030-drops-42884},
  doi =		{10.4230/DFU.Vol5.10452.1},
  annote =	{Keywords: chase, chase termination, data exchange, incomplete information}
}
Document
Algorithms for Core Computation in Data Exchange

Authors: Vadim Savenkov


Abstract
We describe the state of the art in the area of core computation for data exchange. Two main approaches are considered: post-processing core computation, applied to a canonical universal solution constructed by chasing a given schema mapping, and direct core computation, where the mapping is first rewritten in order to create core universal solutions by chasing it.

Cite as

Vadim Savenkov. Algorithms for Core Computation in Data Exchange. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 39-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{savenkov:DFU.Vol5.10452.38,
  author =	{Savenkov, Vadim},
  title =	{{Algorithms for Core Computation in Data Exchange}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{39--68},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.38},
  URN =		{urn:nbn:de:0030-drops-42896},
  doi =		{10.4230/DFU.Vol5.10452.38},
  annote =	{Keywords: Data integration, Data exchange, Core computation}
}
Document
The Inverse of a Schema Mapping

Authors: Jorge Pérez


Abstract
The inversion of schema mappings has been identified as one of the fundamental operators for the development of a general framework for data exchange, data integration, and more generally, for metadata management. Given a mapping M from a schema S to a schema T, an inverse of M is a new mapping that describes the reverse relationship fromT to S, and that is semantically consistent with the relationship previously established by M. In practical scenarios, the inversion of a schema mapping can have several applications. For example, in a data exchange context, if a mapping M is used to exchange data from a source to a target schema, an inverse of M can be used to exchange the data back to the source, thus reversing the application of M. The formalization of a clear semantics for the inverse operator has proved to be a very difficult task. In fact, during the last years, several alternative notions of inversion for schema mappings have been proposed in the literature. This chapter provides a survey on the different formalizations for the inverse operator and the main theoretical and practical results obtained so far. In particular, we present and compare the main proposals for inverting schema mappings that have been considered in the literature. For each one of them we present their formal semantics and characterizations of their existence. We also present algorithms to compute inverses and study the language needed to express such inverses.

Cite as

Jorge Pérez. The Inverse of a Schema Mapping. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 69-95, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{perez:DFU.Vol5.10452.69,
  author =	{P\'{e}rez, Jorge},
  title =	{{The Inverse of a Schema Mapping}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{69--95},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.69},
  URN =		{urn:nbn:de:0030-drops-42909},
  doi =		{10.4230/DFU.Vol5.10452.69},
  annote =	{Keywords: Schema mappings, data exchange, inverse}
}
Document
Reasoning about Schema Mappings

Authors: Emanuel Sallinger


Abstract
Schema mappings are an important tool in several areas of database research. Recently, the topic of reasoning about schema mappings was given attention, in particular revolving around the central concepts of equivalence and optimality. In this chapter, we survey these results. First, we introduce relaxed notions of logical equivalence and show their potential for finding optimized schema mappings. We then look at applications of these concepts to optimization, normalization, and schema mapping management, as well as the boundaries of computability. We conclude by giving a glimpse at reasoning about schema mappings in a broader sense by looking at how to debug schema mappings.

Cite as

Emanuel Sallinger. Reasoning about Schema Mappings. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 97-127, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{sallinger:DFU.Vol5.10452.97,
  author =	{Sallinger, Emanuel},
  title =	{{Reasoning about Schema Mappings}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{97--127},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.97},
  URN =		{urn:nbn:de:0030-drops-42917},
  doi =		{10.4230/DFU.Vol5.10452.97},
  annote =	{Keywords: data exchange, data integration, schema mappings, equivalence, optimality, normalization, schema mapping management}
}
Document
Query Processing in Data Integration

Authors: Paolo Guagliardo and Piotr Wieczorek


Abstract
In this chapter we illustrate the main techniques for processing queries in data integration. The first part of the chapter focuses on the problem of query answering in the relational setting, and describes approaches based on variants of the chase, along with how to deal with integrity constraints and access patterns. The second part of the chapter investigates query processing in the context of semistructured data, which is best described by graph-based data models, where the expressiveness of query languages not common in traditional database systems allows to point out the subtle differences between query answering and query rewriting. The chapter is closed by a very brief discussion of query processing in data integration with XML and ontologies.

Cite as

Paolo Guagliardo and Piotr Wieczorek. Query Processing in Data Integration. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 129-160, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{guagliardo_et_al:DFU.Vol5.10452.129,
  author =	{Guagliardo, Paolo and Wieczorek, Piotr},
  title =	{{Query Processing in Data Integration}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{129--160},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.129},
  URN =		{urn:nbn:de:0030-drops-42929},
  doi =		{10.4230/DFU.Vol5.10452.129},
  annote =	{Keywords: Query processing, Data integration, Relational data, Semistructured data}
}
Document
Semantics for Non-Monotone Queries in Data Exchange and Data Integration

Authors: André Hernich


Abstract
A fundamental question in data exchange and data integration is how to answer queries that are posed against the target schema, or the global schema, respectively. While the certain answers semantics has proved to be adequate for answering monotone queries, the question concerning an appropriate semantics for non-monotone queries turned out to be more difficult. This article surveys approaches and semantics for answering non-monotone queries in data exchange and data integration.

Cite as

André Hernich. Semantics for Non-Monotone Queries in Data Exchange and Data Integration. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 161-184, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{hernich:DFU.Vol5.10452.161,
  author =	{Hernich, Andr\'{e}},
  title =	{{Semantics for Non-Monotone Queries in Data Exchange and Data Integration}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{161--184},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.161},
  URN =		{urn:nbn:de:0030-drops-42936},
  doi =		{10.4230/DFU.Vol5.10452.161},
  annote =	{Keywords: certain answers, closed world assumption, deductive databases, universal solutions, core}
}
Document
Peer Data Management

Authors: Armin Roth and Sebastian Skritek


Abstract
Peer Data Management (PDM) deals with the management of structured data in unstructured peer-to-peer (P2P) networks. Each peer can store data locally and define relationships between its data and the data provided by other peers. Queries posed to any of the peers are then answered by also considering the information implied by those mappings. The overall goal of PDM is to provide semantically well-founded integration and exchange of heterogeneous and distributed data sources. Unlike traditional data integration systems, peer data management systems (PDMSs) thereby allow for full autonomy of each member and need no central coordinator. The promise of such systems is to provide flexible data integration and exchange at low setup and maintenance costs. However, building such systems raises many challenges. Beside the obvious scalability problem, choosing an appropriate semantics that can deal with arbitrary, even cyclic topologies, data inconsistencies, or updates while at the same time allowing for tractable reasoning has been an area of active research in the last decade. In this survey we provide an overview of the different approaches suggested in the literature to tackle these problems, focusing on appropriate semantics for query answering and data exchange rather than on implementation specific problems.

Cite as

Armin Roth and Sebastian Skritek. Peer Data Management. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 185-215, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{roth_et_al:DFU.Vol5.10452.185,
  author =	{Roth, Armin and Skritek, Sebastian},
  title =	{{Peer Data Management}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{185--215},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.185},
  URN =		{urn:nbn:de:0030-drops-42949},
  doi =		{10.4230/DFU.Vol5.10452.185},
  annote =	{Keywords: Peer Data Management, PDM, Peer Data Management Systems, PDMS, Survey, P2P}
}
Document
Management of Inconsistencies in Data Integration

Authors: Ekaterini Ioannou and Slawek Staworko


Abstract
Data integration aims at providing a unified view over data coming from various sources. One of the most challenging tasks for data integration is handling the inconsistencies that appear in the integrated data in an efficient and effective manner. In this chapter, we provide a survey on techniques introduced for handling inconsistencies in data integration, focusing on two groups. The first group contains techniques for computing consistent query answers, and includes mechanisms for the compact representation of repairs, query rewriting, and logic programs. The second group contains techniques focusing on the resolution of inconsistencies. This includes methodologies for computing similarity between atomic values as well as similarity between groups of data, collective techniques, scaling to large datasets, and dealing with uncertainty that is related to inconsistencies.

Cite as

Ekaterini Ioannou and Slawek Staworko. Management of Inconsistencies in Data Integration. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 217-235, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{ioannou_et_al:DFU.Vol5.10452.217,
  author =	{Ioannou, Ekaterini and Staworko, Slawek},
  title =	{{Management of Inconsistencies in Data Integration}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{217--235},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.217},
  URN =		{urn:nbn:de:0030-drops-42952},
  doi =		{10.4230/DFU.Vol5.10452.217},
  annote =	{Keywords: Data integration, Consistent query answers, Resolution of inconsistencies}
}
Document
Algorithmic Techniques for Processing Data Streams

Authors: Elena Ikonomovska and Mariano Zelke


Abstract
We give a survey at some algorithmic techniques for processing data streams. After covering the basic methods of sampling and sketching, we present more evolved procedures that resort on those basic ones. In particular, we examine algorithmic schemes for similarity mining, the concept of group testing, and techniques for clustering and summarizing data streams.

Cite as

Elena Ikonomovska and Mariano Zelke. Algorithmic Techniques for Processing Data Streams. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 237-274, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{ikonomovska_et_al:DFU.Vol5.10452.237,
  author =	{Ikonomovska, Elena and Zelke, Mariano},
  title =	{{Algorithmic Techniques for Processing Data Streams}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{237--274},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.237},
  URN =		{urn:nbn:de:0030-drops-42968},
  doi =		{10.4230/DFU.Vol5.10452.237},
  annote =	{Keywords: streaming algorithm, sampling, sketching, group testing, histogram}
}
Document
Data Stream Management Systems

Authors: Sandra Geisler


Abstract
In many application fields, such as production lines or stock analysis, it is substantial to create and process high amounts of data at high rates. Such continuous data flows with unknown size and end are also called data streams. The processing and analysis of data streams are a challenge for common data management systems as they have to operate and deliver results in real time. Data Stream Management Systems (DSMS), as an advancement of database management systems, have been implemented to deal with these issues. DSMS have to adapt to the notion of data streams on various levels, such as query languages, processing or optimization. In this chapter we give an overview of the basics of data streams, architecture principles of DSMS and the used query languages. Furthermore, we specifically detail data quality aspects in DSMS as these play an important role for various applications based on data streams. Finally, the chapter also includes a list of research and commercial DSMS and their key properties.

Cite as

Sandra Geisler. Data Stream Management Systems. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 275-304, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@InCollection{geisler:DFU.Vol5.10452.275,
  author =	{Geisler, Sandra},
  title =	{{Data Stream Management Systems}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{275--304},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.275},
  URN =		{urn:nbn:de:0030-drops-42975},
  doi =		{10.4230/DFU.Vol5.10452.275},
  annote =	{Keywords: Data Streams, Data Stream Management, Data Quality, Query Languages}
}

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