TeCoRe: temporal conflict resolution in knowledge graphs

The management of uncertainty is crucial when harvesting structured content from unstructured and noisy sources. Knowledge Graphs (kgs), maintaining both numerical and non-numerical facts supported by an underlying schema, are a prominent example. Knowledge Graph management is challenging because: (i) most of existing kgs focus on static data, thus impeding the availability of timewise knowledge; (ii) facts in kgs are usually accompanied by a confidence score, which witnesses how likely it is for them to hold. We demonstrate TeCoRe, a system for temporal infer- ence and conflict resolution in uncertain temporal knowledge graphs (utkgs). At the heart of TeCoRe are two state-of-the-art probabilistic reasoners that are able to deal with temporal constraints efficiently. While one is scalable, the other can cope with more expressive constraints. The demonstration will focus on enabling users and applications to find inconsistencies in utkgs. TeCoRe provides an inter- face allowing to select utkgs and editing constraints; shows the maximal consistent subset of the utkg, and displays statistics (e.g., number of noisy facts removed) about the debugging process

A fuzzy approach for discrete event systems recovery.

International audienceA fuzzy approach for modelling and analysing the recovery activities in discrete event systems is presented. Those essential components of the management of discrete event systems require special reasoning and methods to manage uncertain knowledge. For those purposes, we introduce a tool derived from the fuzzy Petri nets. This tool, inspired from the fault tree, generalizes the defects analysis by a temporal fuzzy approach. The recovery, modelled by a dedicated tool, preserves the fuzzy temporal aspect due to a real time information exchange mechanism provied by the monitoring system

Combining physical-based models and satellite images for the spatio-temporal assessment of soil infiltration capacity

The performance of managed artificial recharge (MAR) facilities by means of surface ponds (SP) is controlled by the temporal evolution of the global infiltration capacity Ic of topsoils. Cost-effective maintenance operations that aim to maintain controlled infiltration values during the activity of the SP require the full knowledge of the spatio-temporal variability of Ic. This task is deemed uncertain. The natural reduction in time of Ic depends on complex physical, biological and chemical reactions that clog the soil pores and has been observed to decay exponentially to an asymptotic non-zero value. Moreover, the relative influence of single clogging processes depend on some initial parameters of the soil, such as the initial infiltration capacity (Ic,0). This property is also uncertain, as aquifers are typically heterogeneous and scarcely characterized in practical situations. We suggest a method to obtain maps of Ic using a geostatistical approach, which is suitable to be extended to engineering risk assessment concerning management of SP facilities. We propose to combine geostatistical inference and a temporally-lumped physical model to reproduce non-uniform clogging in topsoils of a SP, using field campaigns of local and large scale tests and additionally by means of satellite images as secondary information. We then postulate a power-law relationship between the parameter of the exponential law, k, and Ic,0. It is found that calibrating the two parameters of the power law model it is possible to fit the temporal evolution of total infiltration rate at the pond scale in a MAR test facility. The results can be used to design appropriate measures to selectively limit clogging during operation, extending the life of the infiltration pond. The performance of managed artificial recharge (MAR) facilities by means of surface ponds (SP) is controlled by the temporal evolution of the global infiltration capacity Ic of topsoils. Cost-effective maintenance operations that aim to maintain controlled infiltration values during the activity of the SP require the full knowledge of the spatio-temporal variability of Ic. This task is deemed uncertain. The natural reduction in time of Ic depends on complex physical, biological and chemical reactions that clog the soil pores and has been observed to decay exponentially to an asymptotic non-zero value. Moreover, the relative influence of single clogging processes depend on some initial parameters of the soil, such as the initial infiltration capacity (Ic,0). This property is also uncertain, as aquifers are typically heterogeneous and scarcely characterized in practical situations. We suggest a method to obtain maps of Ic using a geostatistical approach, which is suitable to be extended to engineering risk assessment concerning management of SP facilities. We propose to combine geostatistical inference and a temporally-lumped physical model to reproduce non-uniform clogging in topsoils of a SP, using field campaigns of local and large scale tests and additionally by means of satellite images as secondary information. We then postulate a power-law relationship between the parameter of the exponential law, ¿, and Ic,0. It is found that calibrating the two parameters of the power law model it is possible to fit the temporal evolution of total infiltration rate at the pond scale in a MAR test facility. The results can be used to design appropriate measures to selectively limit clogging during operation, extending the life of the infiltration pon

Dura

The reactive event processing language, that is developed in the context of this project, has been called DEAL in previous documents. When we chose this name for our language it has not been used by other authors working in the same research area (complex event processing). However, in the meantime it appears in publications of other authors and because we have not used the name in publications yet we cannot claim that we were the first to use it. In order to avoid ambiguities and name conflicts in future publications we decided to rename our language to Dura which stands for “Declarative uniform reactive event processing language”. Therefore the title of this deliverable has been updated to “Dura – Concepts and Examples”

Time indeterminacy and spatio-temporal building transformations: an approach for architectural heritage understanding

Nowadays most digital reconstructions in architecture and archeology describe buildings heritage as awhole of static and unchangeable entities. However, historical sites can have a rich and complex history, sometimes full of evolutions, sometimes only partially known by means of documentary sources. Various aspects condition the analysis and the interpretation of cultural heritage. First of all, buildings are not inexorably constant in time: creation, destruction, union, division, annexation, partial demolition and change of function are the transformations that buildings can undergo over time. Moreover, other factors sometimes contradictory can condition the knowledge about an historical site, such as historical sources and uncertainty. On one hand, historical documentation concerning past states can be heterogeneous, dubious, incomplete and even contradictory. On the other hand, uncertainty is prevalent in cultural heritage in various forms: sometimes it is impossible to define the dating period, sometimes the building original shape or yet its spatial position. This paper proposes amodeling approach of the geometrical representation of buildings, taking into account the kind of transformations and the notion of temporal indetermination

A general framework for quantifying the effects of land-use history on ecosystem dynamics

Land-use legacies are important for explaining present-day ecological patterns and processes. However, an overarching approach to quantify land-use history effects on ecosystem properties is lacking, mainly due to the scarcity of high-quality, complete and detailed data on past land use. We propose a general framework for quantifying the effects of land-use history on ecosystem properties, which is applicable (i) to different ecological processes in various ecosystem types and across trophic levels; and (ii) when historical data are incomplete or of variable quality. The conceptual foundation of our framework is that past land use affects current (and future) ecosystem properties through altering the past values of resources and conditions that are the driving variables of ecosystem responses. We describe and illustrate how Markov chains can be applied to derive past time series of driving variables, and how these time series can be used to improve our understanding of present-day ecosystem properties. We present our framework in a stepwise manner, elucidating its general nature. We illustrate its application through a case study on the importance of past light levels for the contemporary understorey composition of temperate deciduous forest. We found that the understorey shows legacies of past forest management: high past light availability lead to a low proportion of typical forest species in the understorey. Our framework can be a useful tool for quantifying the effect of past land use on ecological patterns and processes and enhancing our understanding of ecosystem dynamics by including legacy effects which have often been ignored

Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams

Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology