259 research outputs found
Semantic Query Reformulation in Social PDMS
We consider social peer-to-peer data management systems (PDMS), where each
peer maintains both semantic mappings between its schema and some
acquaintances, and social links with peer friends. In this context,
reformulating a query from a peer's schema into other peer's schemas is a hard
problem, as it may generate as many rewritings as the set of mappings from that
peer to the outside and transitively on, by eventually traversing the entire
network. However, not all the obtained rewritings are relevant to a given
query. In this paper, we address this problem by inspecting semantic mappings
and social links to find only relevant rewritings. We propose a new notion of
'relevance' of a query with respect to a mapping, and, based on this notion, a
new semantic query reformulation approach for social PDMS, which achieves great
accuracy and flexibility. To find rapidly the most interesting mappings, we
combine several techniques: (i) social links are expressed as FOAF (Friend of a
Friend) links to characterize peer's friendship and compact mapping summaries
are used to obtain mapping descriptions; (ii) local semantic views are special
views that contain information about external mappings; and (iii) gossiping
techniques improve the search of relevant mappings. Our experimental
evaluation, based on a prototype on top of PeerSim and a simulated network
demonstrate that our solution yields greater recall, compared to traditional
query translation approaches proposed in the literature.Comment: 29 pages, 8 figures, query rewriting in PDM
View Selection in Semantic Web Databases
We consider the setting of a Semantic Web database, containing both explicit
data encoded in RDF triples, and implicit data, implied by the RDF semantics.
Based on a query workload, we address the problem of selecting a set of views
to be materialized in the database, minimizing a combination of query
processing, view storage, and view maintenance costs. Starting from an existing
relational view selection method, we devise new algorithms for recommending
view sets, and show that they scale significantly beyond the existing
relational ones when adapted to the RDF context. To account for implicit
triples in query answers, we propose a novel RDF query reformulation algorithm
and an innovative way of incorporating it into view selection in order to avoid
a combinatorial explosion in the complexity of the selection process. The
interest of our techniques is demonstrated through a set of experiments.Comment: VLDB201
Ontology-based data access with databases: a short course
Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop
Towards Intelligent Databases
This article is a presentation of the objectives and techniques
of deductive databases. The deductive approach to databases aims at extending
with intensional definitions other database paradigms that describe
applications extensionaUy. We first show how constructive specifications can
be expressed with deduction rules, and how normative conditions can be defined
using integrity constraints. We outline the principles of bottom-up and
top-down query answering procedures and present the techniques used for
integrity checking. We then argue that it is often desirable to manage with
a database system not only database applications, but also specifications of
system components. We present such meta-level specifications and discuss
their advantages over conventional approaches
Doctor of Philosophy
dissertationLinked data are the de-facto standard in publishing and sharing data on the web. To date, we have been inundated with large amounts of ever-increasing linked data in constantly evolving structures. The proliferation of the data and the need to access and harvest knowledge from distributed data sources motivate us to revisit several classic problems in query processing and query optimization. The problem of answering queries over views is commonly encountered in a number of settings, including while enforcing security policies to access linked data, or when integrating data from disparate sources. We approach this problem by efficiently rewriting queries over the views to equivalent queries over the underlying linked data, thus avoiding the costs entailed by view materialization and maintenance. An outstanding problem of query rewriting is the number of rewritten queries is exponential to the size of the query and the views, which motivates us to study problem of multiquery optimization in the context of linked data. Our solutions are declarative and make no assumption for the underlying storage, i.e., being store-independent. Unlike relational and XML data, linked data are schema-less. While tracking the evolution of schema for linked data is hard, keyword search is an ideal tool to perform data integration. Existing works make crippling assumptions for the data and hence fall short in handling massive linked data with tens to hundreds of millions of facts. Our study for keyword search on linked data brought together the classical techniques in the literature and our novel ideas, which leads to much better query efficiency and quality of the results. Linked data also contain rich temporal semantics. To cope with the ever-increasing data, we have investigated how to partition and store large temporal or multiversion linked data for distributed and parallel computation, in an effort to achieve load-balancing to support scalable data analytics for massive linked data
Rewriting Complex Queries from Cloud to Fog under Capability Constraints to Protect the Users' Privacy
In this paper we show how existing query rewriting and query containment techniques can be used to achieve an efficient and privacy-aware processing of queries. To achieve this, the whole network structure, from data producing sensors up to cloud computers, is utilized to create a database machine consisting of billions of devices from the Internet of Things. Based on previous research in the field of database theory, especially query rewriting, we present a concept to split a query into fragment and remainder queries. Fragment queries can operate on resource limited devices to filter and preaggregate data. Remainder queries take these data and execute the last, complex part of the original queries on more powerful devices. As a result, less data is processed and forwarded in the network and the privacy principle of data minimization is accomplished
Automatic physical database design : recommending materialized views
This work discusses physical database design while focusing on the problem of selecting materialized views for improving the performance of a database system. We first address the satisfiability and implication problems for mixed arithmetic constraints. The results are used to support the construction of a search space for view selection problems. We proposed an approach for constructing a search space based on identifying maximum commonalities among queries and on rewriting queries using views. These commonalities are used to define candidate views for materialization from which an optimal or near-optimal set can be chosen as a solution to the view selection problem. Using a search space constructed this way, we address a specific instance of the view selection problem that aims at minimizing the view maintenance cost of multiple materialized views using multi-query optimization techniques. Further, we study this same problem in the context of a commercial database management system in the presence of memory and time restrictions. We also suggest a heuristic approach for maintaining the views while guaranteeing that the restrictions are satisfied. Finally, we consider a dynamic version of the view selection problem where the workload is a sequence of query and update statements. In this case, the views can be created (materialized) and dropped during the execution of the workload. We have implemented our approaches to the dynamic view selection problem and performed extensive experimental testing. Our experiments show that our approaches perform in most cases better than previous ones in terms of effectiveness and efficiency
Tree-like Queries in OWL 2 QL: Succinctness and Complexity Results
This paper investigates the impact of query topology on the difficulty of
answering conjunctive queries in the presence of OWL 2 QL ontologies. Our first
contribution is to clarify the worst-case size of positive existential (PE),
non-recursive Datalog (NDL), and first-order (FO) rewritings for various
classes of tree-like conjunctive queries, ranging from linear queries to
bounded treewidth queries. Perhaps our most surprising result is a
superpolynomial lower bound on the size of PE-rewritings that holds already for
linear queries and ontologies of depth 2. More positively, we show that
polynomial-size NDL-rewritings always exist for tree-shaped queries with a
bounded number of leaves (and arbitrary ontologies), and for bounded treewidth
queries paired with bounded depth ontologies. For FO-rewritings, we equate the
existence of polysize rewritings with well-known problems in Boolean circuit
complexity. As our second contribution, we analyze the computational complexity
of query answering and establish tractability results (either NL- or
LOGCFL-completeness) for a range of query-ontology pairs. Combining our new
results with those from the literature yields a complete picture of the
succinctness and complexity landscapes for the considered classes of queries
and ontologies.Comment: This is an extended version of a paper accepted at LICS'15. It
contains both succinctness and complexity results and adopts FOL notation.
The appendix contains proofs that had to be omitted from the conference
version for lack of space. The previous arxiv version (a long version of our
DL'14 workshop paper) only contained the succinctness results and used
description logic notatio
The ViP2P Platform: XML Views in P2P
The growing volumes of XML data sources on the Web or produced by
enterprises, organizations etc. raise many performance challenges for data
management applications. In this work, we are concerned with the distributed,
peer-to-peer management of large corpora of XML documents, based on distributed
hash table (or DHT, in short) overlay networks. We present ViP2P (standing for
Views in Peer-to-Peer), a distributed platform for sharing XML documents based
on a structured P2P network infrastructure (DHT). At the core of ViP2P stand
distributed materialized XML views, defined by arbitrary XML queries, filled in
with data published anywhere in the network, and exploited to efficiently
answer queries issued by any network peer. ViP2P allows user queries to be
evaluated over XML documents published by peers in two modes. First, a
long-running subscription mode, when a query can be registered in the system
and receive answers incrementally when and if published data matches the query.
Second, queries can also be asked in an ad-hoc, snapshot mode, where results
are required immediately and must be computed based on the results of other
long-running, subscription queries. ViP2P innovates over other similar
DHT-based XML sharing platforms by using a very expressive structured XML query
language. This expressivity leads to a very flexible distribution of XML
content in the ViP2P network, and to efficient snapshot query execution. ViP2P
has been tested in real deployments of hundreds of computers. We present the
platform architecture, its internal algorithms, and demonstrate its efficiency
and scalability through a set of experiments. Our experimental results outgrow
by orders of magnitude similar competitor systems in terms of data volumes,
network size and data dissemination throughput.Comment: RR-7812 (2011
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