3,250 research outputs found
Mapping-equivalence and oid-equivalence of single-function object-creating conjunctive queries
Conjunctive database queries have been extended with a mechanism for object
creation to capture important applications such as data exchange, data
integration, and ontology-based data access. Object creation generates new
object identifiers in the result, that do not belong to the set of constants in
the source database. The new object identifiers can be also seen as Skolem
terms. Hence, object-creating conjunctive queries can also be regarded as
restricted second-order tuple-generating dependencies (SO tgds), considered in
the data exchange literature.
In this paper, we focus on the class of single-function object-creating
conjunctive queries, or sifo CQs for short. We give a new characterization for
oid-equivalence of sifo CQs that is simpler than the one given by Hull and
Yoshikawa and places the problem in the complexity class NP. Our
characterization is based on Cohen's equivalence notions for conjunctive
queries with multiplicities. We also solve the logical entailment problem for
sifo CQs, showing that also this problem belongs to NP. Results by Pichler et
al. have shown that logical equivalence for more general classes of SO tgds is
either undecidable or decidable with as yet unknown complexity upper bounds.Comment: This revised version has been accepted on 11 January 2016 for
publication in The VLDB Journa
Solving the TTC 2011 Reengineering Case with GReTL
This paper discusses the GReTL reference solution of the TTC 2011
Reengineering case. Given a Java syntax graph, a simple state machine model has
to be extracted. The submitted solution covers both the core task and the two
extension tasks.Comment: In Proceedings TTC 2011, arXiv:1111.440
Query-based comparison of OBDA specifications
An ontology-based data access (OBDA) system is composed of one or more data sources, an ontology that provides a conceptual view of the data, and declarative mappings that relate the data and ontology schemas. In order to debug and optimize such systems, it is important to be able to analyze and compare OBDA specifications. Recent work in this direction compared specifications using classical notions of equivalence and entailment, but an interesting alternative is to consider query-based notions, in which two specifications are deemed equivalent if they give the same answers to the considered query or class of queries for all possible data sources. In this paper, we define such query-based notions of entailment and equivalence of OBDA specifications and investigate the complexity of the resulting analysis tasks when the ontology is formulated in DL-LiteR
Explain3D: Explaining Disagreements in Disjoint Datasets
Data plays an important role in applications, analytic processes, and many
aspects of human activity. As data grows in size and complexity, we are met
with an imperative need for tools that promote understanding and explanations
over data-related operations. Data management research on explanations has
focused on the assumption that data resides in a single dataset, under one
common schema. But the reality of today's data is that it is frequently
un-integrated, coming from different sources with different schemas. When
different datasets provide different answers to semantically similar questions,
understanding the reasons for the discrepancies is challenging and cannot be
handled by the existing single-dataset solutions.
In this paper, we propose Explain3D, a framework for explaining the
disagreements across disjoint datasets (3D). Explain3D focuses on identifying
the reasons for the differences in the results of two semantically similar
queries operating on two datasets with potentially different schemas. Our
framework leverages the queries to perform a semantic mapping across the
relevant parts of their provenance; discrepancies in this mapping point to
causes of the queries' differences. Exploiting the queries gives Explain3D an
edge over traditional schema matching and record linkage techniques, which are
query-agnostic. Our work makes the following contributions: (1) We formalize
the problem of deriving optimal explanations for the differences of the results
of semantically similar queries over disjoint datasets. (2) We design a 3-stage
framework for solving the optimal explanation problem. (3) We develop a
smart-partitioning optimizer that improves the efficiency of the framework by
orders of magnitude. (4)~We experiment with real-world and synthetic data to
demonstrate that Explain3D can derive precise explanations efficiently
UML to XML-Schema Transformation: a Case Study in Managing Alternative Model Transformations in MDA
In a Model Driven Architecture (MDA) software development process, models are\ud
repeatedly transformed to other models in order to finally achieve a set of models with enough details to implement a system. Generally, there are multiple ways to transform one model into another model. Alternative target models differ in their quality properties and the selection of a particular model is determined on the basis of specific requirements. Software engineers must be able to identify, compare and select the appropriate transformations within the given set of requirements. The current transformation languages used for describing and executing model transformations only provide means to specify the transformations but do not help to identify and select from the alternative transformations. In this paper we propose a process and a set of techniques for constructing a transformation space for a given transformation problem. The process uses a source model, its meta-model and the meta-model of the target as input and generates a transformation space. Every element in that space represents a transformation that produces a result that is an instance of the target meta-model. The requirements that must be fulfilled by the result are captured and represented in a quality model. We explain our approach using an illustrative example for transforming a platform independent model expressed in UML into platform specific models that represent XML schemas. A particular quality model of extensibility is presented in the paper
Simulation Subsumption or Déjà vu on the Web
Simulation unification is a special kind of unification adapted to retrieving semi-structured data on the Web. This article introduces simulation subsumption, or containment, that is, query subsumption under simulation unification. Simulation subsumption is crucial in general for query optimization, in particular for optimizing pattern-based search engines, and for the termination of recursive rule-based web languages such as the XML and RDF query language Xcerpt. This paper first motivates and formalizes simulation subsumption. Then, it establishes decidability of simulation subsumption for advanced query patterns featuring descendant constructs, regular expressions, negative subterms (or subterm exclusions), and multiple variable occurrences. Finally, we show that subsumption between two query terms can be decided in O(n!n) where n is the sum of the sizes of both query terms
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