140 research outputs found
Tailoring temporal description logics for reasoning over temporal conceptual models
Temporal data models have been used to describe how data can evolve in the context of temporal databases. Both the Extended Entity-Relationship (EER) model and the Unified Modelling Language (UML) have been temporally extended to design temporal databases. To automatically check quality properties of conceptual schemas various encoding to Description Logics (DLs) have been proposed in the literature. On the other hand, reasoning on temporally extended DLs turn out to be too complex for effective reasoning ranging from 2ExpTime up to undecidable languages. We propose here to temporalize the âlight-weightâ DL-Lite logics obtaining nice computational results while still being able to represent various constraints of temporal conceptual models. In particular, we consider temporal extensions of DL-Lite^N_bool, which was shown to be adequate for capturing non-temporal conceptual models without relationship inclusion, and its fragment DL-Lite^N_core with most primitive concept inclusions, which are nevertheless enough to represent almost all types of atemporal constraints (apart from
covering)
Stellar feedback from HMXBs in cosmological hydrodynamical simulations
We explored the role of X-ray binaries composed by a black hole and a massive
stellar companion (BHXs) as sources of kinetic feedback by using hydrodynamical
cosmological simulations. Following previous results, our BHX model selects low
metal-poor stars () as possible progenitors. The model that
better reproduces observations assumes that a fraction of
low-metallicity black holes are in binary systems which produce BHXs. These
sources are estimated to deposit erg of kinetic energy per
event. With these parameters and in the simulated volume, we find that the
energy injected by BHXs represents of the total energy released by
SNII and BHX events at redshift and then decreases rapidly as baryons
get chemically enriched. Haloes with virial masses smaller than (or K) are the most directly affected
ones by BHX feedback. These haloes host galaxies with stellar masses in the
range M. Our results show that BHX feedback is able to
keep the interstellar medium warm, without removing a significant gas fraction,
in agreement with previous analytical calculations. Consequently, the
stellar-to-dark matter mass ratio is better reproduced at high redshift. Our
model also predicts a stronger evolution of the number of galaxies as a
function of the stellar mass with redshift when BHX feedback is considered.
These findings support previous claims that the BHXs could be an effective
source of feedback in early stages of galaxy evolution.Comment: 11 pages, 8 figures, accepted for publication in MNRA
Evolving Objects in Temporal Information Systems
This paper presents a semantic foundation of temporal conceptual models used to design temporal information systems. We consider a modelling language able to express both timestamping and evolution constraints. We conduct a deeper investigation of evolution constraints, eventually devising a model-theoretic semantics for a full-fledged model with both timestamping and evolution constraints. The proposed formalization is meant both to clarify the meaning of the various temporal constructors that appeared in the literature and to give a rigorous definition, in the context of temporal information systems, to notions like satisfiability, subsumption and logical implication. Furthermore, we show how to express temporal constraints using a subset of first-order temporal logic, i.e. DLRUS, the description logic DLR extended with the temporal operators Since and Until. We show how DLRUS is able to capture the various modelling constraints in a succinct way and to perform automated reasoning on temporal conceptual models
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
Modal Logics of Topological Relations
Logical formalisms for reasoning about relations between spatial regions play
a fundamental role in geographical information systems, spatial and constraint
databases, and spatial reasoning in AI. In analogy with Halpern and Shoham's
modal logic of time intervals based on the Allen relations, we introduce a
family of modal logics equipped with eight modal operators that are interpreted
by the Egenhofer-Franzosa (or RCC8) relations between regions in topological
spaces such as the real plane. We investigate the expressive power and
computational complexity of logics obtained in this way. It turns out that our
modal logics have the same expressive power as the two-variable fragment of
first-order logic, but are exponentially less succinct. The complexity ranges
from (undecidable and) recursively enumerable to highly undecidable, where the
recursively enumerable logics are obtained by considering substructures of
structures induced by topological spaces. As our undecidability results also
capture logics based on the real line, they improve upon undecidability results
for interval temporal logics by Halpern and Shoham. We also analyze modal
logics based on the five RCC5 relations, with similar results regarding the
expressive power, but weaker results regarding the complexity
SOWL QL: Querying Spatio - Temporal Ontologies in OWL
We introduce SOWL QL, a query language for spatio-temporal information in ontologies. Buildingupon
SOWL (Spatio-Temporal OWL), an ontology for handling spatio-temporal information in OWL, SOWL QL supports querying over qualitative spatio-temporal information (expressed using natural language expressions such as âbeforeâ, âafterâ, ânorth ofâ, âsouth ofâ) rather than merely quantitative information (exact dates,
times, locations). SOWL QL extends SPARQL with a powerful set of temporal and spatial operators, including temporal Allen topological, spatial directional and topological operations or combinations of the above.
SOWL QL maintains simplicity of expression and also, upward and downward compatibility with SPARQL. Query translation in SOWL QL yields SPARQL queries implying that, querying spatio-temporal ontologies using SPARQL is still feasible but suffers from several drawbacks the most important of them being that, queries in SPARQL become particularly complicated and users must be familiar with the underlying spatio-temporal representation (the âN-ary relationsâ or the â4D-fluentsâ approach in this work). Finally, querying in SOWL QL is supported by the SOWL reasoner which is not part of the standard SPARQL translation. The run-time performance of SOWL QL has been assessed experimentally in a real data setting. A critical analysis of its performance is also presented
Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea
Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980â2013 and a detailed multi-indicator description of the period 2007â2013. Then a 1980â2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies
Relating some stuff to other stuff
Traceability in food and medicine supply chains has to handle stuffsâentities such as milk and starch indicated with mass nounsâand their portions and parts that get separated and put together to make the final product. Implementations have underspecified âlinksâ, if at all, and theoretical accounts from philosophy and in domain ontologies are incomplete as regards the relations involved. To solve this issue, we define seven relations for portions and stuff-parts, which are temporal where needed. The resulting
theory distinguishes between the extensional and intensional level, and between amount of stuff and quantity. With application trade-offs, this has been implemented as an extension to the Stuff Ontology core ontology that now also imports a special purpose module of the Ontology of units of Measure for quantities. Although atemporal, some automated reasoning for traceability is still possible thanks to using property chains to approximate the relevant temporal aspects
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