Enhancing CIDOC-CRM Models for GeoSPARQL Processing with MapReduce

Spatial and temporal dimensions are two important characteristics of archaeological data and cultural heritage in general. The ability to perform some sort of reasoning on them is crucial during the analysis and interpretation process performed by domain experts. Many models have been defined in literature in order to properly describe such data and support the following interpretation process; among them, CIDOC CRM is a formal ontology specifically developed to represent cultural heritage information and many extensions have been proposed in recent years in order to enrich such model. In particular, CRMgeo tries to bring the gap between the cultural heritage domain and the geo-spatial domain, by providing a link towards GeoSPARQL and by defining the necessary constructs for the representation of spatial data types and relations. Unfortunately, the current support to the process of spatial functions through SPARQL query engine is still limited and many performance problems remain. The aim of this paper is twofold: (i) to evaluate the applicability of CRMgeo in representing spatial characteristics and relations of archaeological objects, and (2) to propose a MapReduce procedure able to efficiently derive spatial relations between objects, in order to automatically enhance an RDF model with them and avoid the performance issues derived from the use of GeoSPARQL query engine

Efficient Management for Geospatial and Temporal Data using Ontology-based Data Access Techniques

Το μοντέλο δεδομένων RDF και η γλώσσα επερωτήσεων SPARQL είναι ευρέως διαδεδομένα για την χρήση τους με σκοπό την ενοποίηση πληροφορίας που προέρχεται από διαφορετικές πηγές. Ο αυξανόμενος αριθμός των γεωχωρικών συνόλων δεδομένων που είναι πλέον διαθέσιμα σαν γεωχωρικά διασυνδεδεμένα δεδομένα οδήγησε στην εμφάνιση επεκτάσεων του μοντέλου δεδομένων RDF και της γλώσσας επερωτήσεων SPARQL. Δύο από τις σημαντικότερες επεκτάσεις αυτές είναι η γλώσσα GeoSPARQL, η οποία έγινε OGC πρότυπο, και το πλαίσιο του μοντέλου δεδομένων stRDF και της γλώσσας επερωτήσεων stSPARQL. Και οι δύο προσεγγίσεις μπορούν να χρησιμοποιηθούν για την αναπαράσταση και επερώτηση διασυνδεδεμένων γεωχωρικών δεδομένων, ενώ το μοντέλο stRDF και η γλώσσα stSPARQL παρέχουν επίσης επιπλέον λειτουργικότητα για την αναπαράσταση και επερώτηση χρονικών δεδομένων. Παρότι ο αριθμός των δεδομένων που είναι διαθέσιμα σαν γεωχωρικά ή και χρονικά διασυνδεδεμένα δεδομένα αυξάνεται, η μετατροπή των γεωχωρικών δεδομένων σε RDF και η αποθήκευσή τους σε αποθετήρια RDF δεν είναι πάντα η βέλτιστη λύση, ειδικά όταν τα δεδομένα βρίσκονται εξαρχής σε σχεσιακές βάσεις οι οποίες μπορεί να έχουν αρκετά μεγάλο μέγεθος ή και να ενημερώνονται πολύ συχνά. Στα πλαίσια αυτής της διδακτορικής διατριβής, προτείνουμε μια λύση βασισμένη στην ανάκτηση πληροφορίας με χρήση οντολογιών και αντιστοιχίσεων για την επερώτηση δεδομένων πάνω από γεωχωρικές σχεσιακές βάσεις δεδομένων. Επεκτείνουμε τεχνικές επανεγγραφής GeoSPARQL ερωτημάτων σε SQL ώστε η αποτίμηση των επερωτήσεων να γίνεται εξολοκλήρου στο γεωχωρικό σύστημα διαχείρισης βάσεων δεδομένων. Επίσης, εισαγάγουμε επιπλέον λειτουργικότητα στη χρονική συνιστώσα του μοντέλου δεδομένων stRDF και της γλώσσας επερωτήσεων stSPARQL, προκειμένου να διευκολυνθεί η υποστήριξη χρονικών τελεστών σε συστήματα OBDA. Στη συνέχεια, επεκτείνουμε τις παραπάνω μεθόδους με την υποστήριξη διαφορετικών πηγών δεδομένων πέρα από σχεσιακές βάσεις και παρουσιάζουμε μια OBDA προσέγγιση που επιτρέπει τη δημιουργία εικονικών RDF γράφων πάνω από δεδομένα που βρίσκονται διαθέσιμα στο διαδίκτυο σε διάφορες μορφές (πχ. HTML πίνακες, web διεπαφές), με χρήση οντολογιών και αντιστοιχίσεων. Συγκρίναμε την απόδοση του συστήματός μας με ένα σχετικό σύστημα και τα αποτελέσματα έδειξαν ότι πέραν του ότι το σύστημά μας παρέχει μεγαλύτερη λειτουργικότητα (πχ. υποστηρίζει περισσότερα είδη πηγών δεδομένων, περιλαμβάνει απλούστερες διαδικασίες και εξασφαλίζει καλύτερη απόδοση. Τέλος, παρουσιάζουμε την εφαρμογή των μεθόδων και συστημάτων που περιγράφονται στη διατριβή σε πραγματικά σενάρια χρήσης.The data model RDF and query language SPARQL have been widely used for the integration of data coming from different souces. Due to the increasing number of geospatial datasets that are being available as linked open data, a lot of effort focuses in the development of geospatial (and temporal, accordingly) extensions of the framework of RDF and SPARQL. Two highlights of these efforts are the query language GeoSPARQL, that is an OGC standard, and the framework of stRDF and stSPARQL. Both frameworks can be used for the representation and querying of linked geospatial data, and stSPARQL also includes a temporal dimension. Although a lot of geospatial (and some temporal) RDF stores started to emerge, converting geospatial data into RDF and then storing it into an RDF stores is not always best practice, especially when the data exists in a relational database that is fairly large and/or it gets updated frequently. In this thesis, we propose an Ontology-based Data Access (OBDA) approach for accessing geospatial data stored in geospatial relational databases, using the OGC standard GeoSPARQL and R2RML or OBDA mappings. We introduce extensions to an existing SPARQL-to-SQL translation method to support GeoSPARQL features. We describe the implementation of our approach in the system Ontop-spatial, an extension of the OBDA system Ontop for creating virtual geospatial RDF graphs on top of geospatial relational databases. Ontop-spatial is the first geospatial OBDA system and outperforms state-of-the-art geospatial RDF stores. We also show how to answer queries with temproal operators in the OBDA framework, by utilizing the framework stRDF and the query language stSPARQL which we extend with some new features. Next, we extend the data sources supported by Ontop-spatial going beyond relational database management systems, and we present our OBDA solutions for creating virtual RDF graphs on top of various web data sources (e.g., HTML tables, Web APIs) using ontologies and mappings. We compared the performance of our approach with a related implementation and evaluation results showed that not only does Ontop-spatial support more functionalities (e.g., more data sources, more simple workflow), but it also achieves better performance. Last, we describe how the work described in this thesis is applied in real-world application scenarios

Data integration in the rail domain

The exchange of information is crucial to the operation of railways; starting with the distribution of timetables, information must constantly be exchanged in any railway network. The slow evolution of the information environment within the rail industry has resulted in the existence of a diverse range of systems, only able to exchange information essential to railway operations. Were the cost of data integration reduced, then further cost reductions and improvements to customer service would follow as barriers to the adoption of other technologies are removed. The need for data integration has already been studied extensively and has been included in the UK industry's rail technical strategy however, despite it's identification as a key technique for improving integration, uptake of ontology remains limited. This thesis considers techniques to reduce barriers to the take up of ontology in the UK rail industry, and presents a case study in which these techniques are applied. Amongst the key barriers to uptake identified are a lack of software engineers with ontology experience, and the diverse information environment within the rail domain. Techniques to overcomes these barriers using software based tools are considered, and example tools produced which aid the overcoming of these barriers. The case study presented is of a degraded mode signalling system, drawing data from a range of diverse sources, integrated using an ontology. Tools created to improve data integration are employed in this commercial project, successfully combing signalling data with (simulated) train positioning data

Spatial ontologies for architectural heritage

Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

Spatial ontologies for architectural heritage

Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

P-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud

Increasingly data on the Web is stored in the form of Semantic Web data. Because of today's information overload, it becomes very important to store and query these big datasets in a scalable way and hence in a distributed fashion. Cloud Computing offers such a distributed environment with dynamic reallocation of computing and storing resources based on needs. In this work we introduce a scalable distributed Semantic Web database in the Cloud. In order to reduce the number of (unnecessary) intermediate results early, we apply bloom filters. Instead of computing bloom filters, a time-consuming task during query processing as it has been done traditionally, we precompute the bloom filters as much as possible and store them in the indices besides the data. The experimental results with data sets up to 1 billion triples show that our approach speeds up query processing significantly and sometimes even reduces the processing time to less than half

Across Space and Time. Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

This volume presents a selection of the best papers presented at the forty-first annual Conference on Computer Applications and Quantitative Methods in Archaeology. The theme for the conference was "Across Space and Time", and the papers explore a multitude of topics related to that concept, including databases, the semantic Web, geographical information systems, data collection and management, and more