Promoting data provenance tracking in the archaeological interpretation process

n this paper we propose a model and a set of derivation rules for tracking data provenance during the archaeological interpretation process. The interpretation process is the main task performed by an archaeologist that, starting from ground data about evidences and findings, tries to derive knowledge about an ancient object or event. In particular, in this work we concentrate on the dating process used by archaeologists to assign one or more time intervals to a finding in order to define its lifespan on the temporal axis and we propose a framework to represent such information and infer new knowledge including provenance of data. Archaeological data, and in particular their temporal dimension, are typically vague, since many different interpretations can coexist, thus we will use Fuzzy Logic to assign a degree of confidence to values and Fuzzy Temporal Constraint Networks to model relationships between dating of different finding

Distributing Tourists Among POIs with an Adaptive Trip Recommendation System

Traveling is part of many people leisure activities and an increasing fraction of the economy comes from the tourism. Given a destination, the information about the different attractions, or points of interest (POIs), can be found on many sources. Among these attractions, finding the ones that could be of interest for a specific user represents a challenging task. Travel recommendation systems deal with this type of problems. Most of the solution in the literature does not take into account the impact of the suggestions on the level of crowding of POIs. This paper considers the trip planning problem focusing on user balancing among the different POIs. To this aim, we consider the effects of the previous recommendations, as well as estimates based on historical data, while devising a new recommendation. The problem is formulated as a multi-objective optimization problem, and a recommendation engine has been designed and implemented for exploring the solution space in near real-time, through a distributed version of the Simulated Annealing approach. We test our solution using a real dataset of users visiting the POIs of a touristic city, and we show that we are able to provide high quality recommendations, yet maintaining the attractions not overcrowded

Tracking Data Provenance of Archaeological Temporal Information in Presence of Uncertainty

The interpretation process is one of the main tasks performed by archaeologists who, starting from ground data about evidences and findings, incrementally derive knowledge about ancient objects or events. Very often more than one archaeologist contributes in different time instants to discover details about the same finding and thus, it is important to keep track of history and provenance of the overall knowledge discovery process. To this aim, we propose a model and a set of derivation rules for tracking and refining data provenance during the archaeological interpretation process. In particular, among all the possible interpretation activities, we concentrate on the one concerning the dating that archaeologists perform to assign one or more time intervals to a finding to define its lifespan on the temporal axis. In this context, we propose a framework to represent and derive updated provenance data about temporal information after the mentioned derivation process. Archaeological data, and in particular their temporal dimension, are typically vague, since many different interpretations can coexist, thus, we will use Fuzzy Logic to assign a degree of confidence to values and Fuzzy Temporal Constraint Networks to model relationships between dating of different findings represented as a graph-based dataset. The derivation rules used to infer more precise temporal intervals are enriched to manage also provenance information and their following updates after a derivation step. A MapReduce version of the path consistency algorithm is also proposed to improve the efficiency of the refining process on big graph-based datasets

An Interoperable Spatio-Temporal Model for Archaeological Data Based on ISO Standard 19100

Archaeological data are characterized by both spatial and temporal dimensions that are often related to each other and are of particular interest during the interpretation process. For this reason, several attempts have been performed in recent years in order to develop a GIS tailored for archaeological data. However, despite the increasing use of information technologies in the archaeological domain, the actual situation is that any agency or research group independently develops its own local database and management application which is isolated from the others. Conversely, the sharing of information and the cooperation between different archaeological agencies or research groups can be particularly useful in order to support the interpretation process by using data discovered in similar situations w.r.t. spatio-temporal or thematic aspects. In the geographical domain, the INSPIRE initiative of European Union tries to support the development of a Spatial Data Infrastructure (SDI) through which several organizations, like public bodies or private companies, with overlapping goals can share data, resources, tools and competencies in an effective way. The aim of this paper is to lay the basis for the development of an Archaeological SDI starting from the experience acquired during the collaboration among several Italian organizations. In particular, the paper proposes a spatio-temporal conceptual model for archaeological data based on the ISO Standards of the 19100 family and promotes the use of the GeoUML methodology in order to put into practice such interoperability. The GeoUML methodology and tools have been enhanced in order to suite the archaeological domain and to automatically produce several useful documents, configuration files and codebase starting from the conceptual specification. The applicability of the spatio-temporal conceptual model and the usefulness of the produced tools have been tested in three different Italian contexts: Rome, Verona and Isola della Scala

Ontologia para representação semântica de indicadores de desempenho considerando aspectos de vaguidade, temporalidade e relacionamento entre indicadores

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2016.Os indicadores são amplamente utilizados pelas organizações como forma de avaliar, medir e classificar o desempenho organizacional. Parte integrante de sistemas de avaliação de desempenho, os indicadores são, muitas vezes, compartilhados ou comparados com diferentes setores internos ou até mesmo com outras organizações. Entretanto, alguns indicadores possuem associada certa vaguidade e imprecisão, carecendo-lhe também de semântica. Desta forma, a presente tese ocupou-se de apresentar um modelo de conhecimento baseado em ontologia e lógica difusa para representar semanticamente e de forma genérica os indicadores, tratando-se a imprecisão e vaguidade, além de contribuir incluindo a percepção da temporalidade e relacionamento entre indicadores. Utilizando-se a metodologia Design Science Research Methodology, o modelo foi considerado adequado, evidenciando, através da realização de entrevistas, a importância da representação da imprecisão, vaguidade, temporalidade e o relacionamento entre diferentes indicadores no contexto de avaliação de desempenho.Abstract: Indicators are widely used by organizations in order to assess, measure and classify organizational performance. Integral part of performance evaluation systems, indicators are often shared or compared among different domestic sectors or even other organizations. However, some indicators have associated certain vagueness and imprecision, as well as lack of semantics. Thus, this thesis held to present a model of knowledge based on ontology and fuzzy logic to represent in a semantic and generic way, with regard to the imprecision and vagueness, and contribute by including the perception of temporality and the relationship between indicators. Using the methodology Design Science Research Methodology, the model it was considered appropriate, showing, by conducting interviews, the importance of representation of imprecision, vagueness, temporality and the relationship between different indicators in the performance measurement context

A Framework for Managing Temporal Dimensions in Archaeological Data

Spatiotemporal data are often expressed in terms of granularities in a granularity system to indicate the measurement units of the data. A granularity system usually consists of a set of granularities that share a “common refined granularity” (CRG) to ensure granular comparison and data conversion within the system. However, if data from multiple granularity systems need to be used in a unified application, it is necessary to extend the data conversion and comparison within a granularity system to those for multiple granularity systems. This paper proposes a formal framework to enable such an extension. The framework involves essentially some preconditions and properties for verifying existence of a CRG and unifying conversions of incongruous semantics, and supports the approach to integrate multiple systems into one processing granular interoperation across systems just like in a single system. Quantification of uncertainty in granularity conversion is also considered to improve the precision of granular comparison

A Framework for Managing Temporal Dimensions in Archaeological Data

Spatiotemporal data are often expressed in terms of granularities in a granularity system to indicate the measurement units of the data. A granularity system usually consists of a set of granularities that share a “common refined granularity” (CRG) to ensure granular comparison and data conversion within the system. However, if data from multiple granularity systems need to be used in a unified application, it is necessary to extend the data conversion and comparison within a granularity system to those for multiple granularity systems. This paper proposes a formal framework to enable such an extension. The framework involves essentially some preconditions and properties for verifying existence of a CRG and unifying conversions of incongruous semantics, and supports the approach to integrate multiple systems into one processing granular interoperation across systems just like in a single system. Quantification of uncertainty in granularity conversion is also considered to improve the precision of granular comparison

21st International Symposium on Temporal Representation and Reasoning, TIME 2014, Verona, Italy, September 8-10, 2014

The proceedings contain 18 papers. The topics discussed include: a tractable generalization of simple temporal networks and its relation to mean payoff games; sound and complete algorithms for checking the dynamic controllability of temporal networks with uncertainty, disjunction and observation; a formal account of planning with flexible timelines; metric propositional neighborhood logic with an equivalence relation; checking interval properties of computations; approximate interval-based temporal dependencies: the complexity landscape; a framework for managing temporal dimensions in archaeological data; lean index structures for snapshot access in transaction-time databases; high-level operations for creation and maintenance of temporal and conventional schema in the tauXSchema framework; summarizability in multiversion data warehouse; fairness with EXPTIME bundled CTL tableau; and partially punctual metric temporal logic is decidable