A multi-set extended relational algebra: a formal approach to a practical issue

The relational data model is based on sets of tuples, i.e. it does not allow duplicate tuples an a relation. Many database languages and systems do require multi-set semantics though, either because of functional requirements or because of the high costs of duplicate removal in database operations. Several proposals have been presented that discuss multi-set semantics. As these proposals tend to be either rather practical, lacking the formal background, or rather formal, lacking the connection to database practice, the gap between theory and practice has not been spanned yet. This paper proposes a complete extended relational algebra with multi-set semantics, having a clear formal background and a close connection to the standard relational algebra. It includes constructs that extend the algebra to a complete sequential database manipulation language that can either be used as a formal background to other multi-set languages like SQL, or as a database manipulation language on its own. The practical usability of the latter option has been demonstrated in the PRISMA/DB database project, where a variant of the language has been used as the primary database languag

Trajectory Representation in Location-Based Services: Problems and Solution

Recently, much work has been done in feasibility studies on services offered to moving objects in an environment equipped with mobile telephony, network technology and GIS. However, despite of all work on GIS and databases, the situations in which the whereabouts of objects are constantly monitored and stored for future analysis are an important class of problems that present-day database/GIS has difficulty to handle. Considering the fact that data about whereabouts of moving objects are acquired in a discrete way, providing the data when no observation is available is a must. Therefore, obtaining a "faithful representation" of trajectories with a sufficient number of discrete (though possibly erroneous) data points is the objective of this research

A Database Interface for Complex Objects

We describe a formal design for a logical query language using psi-terms as data structures to interact effectively and efficiently with a relational database. The structure of psi-terms provides an adequate representation for so-called complex objects. They generalize conventional terms used in logic programming: they are typed attributed structures, ordered thanks to a subtype ordering. Unification of psi-terms is an effective means for integrating multiple inheritance and partial information into a deduction process. We define a compact database representation for psi-terms, representing part of the subtyping relation in the database as well. We describe a retrieval algorithm based on an abstract interpretation of the psi-term unification process and prove its formal correctness. This algorithm is efficient in that it incrementally retrieves only additional facts that are actually needed by a query, and never retrieves the same fact twice

Functionally Specified Distributed Transactions in Co-operative Scenarios

Addresses the problem of specifying co-operative, distributed transactions in a manner that can be subject to verification and testing. Our approach combines the process-algebraic language LOTOS and the object-oriented database modelling language TM to obtain a clear and formal protocol for distributed database transactions meant to describe co-operation scenarios. We argue that a separation of concerns, namely the interaction of database applications on the one hand and data modelling on the other, results in a practical, modular approach that is formally well-founded. An advantage of this is that we may vary over transaction models to support the language combinatio

Semantic enrichment of GPS trajectories

Semantic annotation of GPS trajectories helps us to recognize the interests of the creator of the GPS trajectories. Automating this trajectory annotation circumvents the requirement of additional user input. To annotate the GPS traces automatically, two types of automated input are required: 1) a collection of possible annotations, and 2) a collection of GPS trajectories to annotate.\ud \ud The first type of input can be a set of points of interest (POIs), activities, weather types, etc. This collection is to be provided by an application developer, and can originate from the web, an external knowledge base, or an existing database, for example.\ud \ud The type of annotation that we are interested in, is annotation with visited locations, in order to create a user profile at a later stage. We have collected POIs by scraping the web, using a self-configuring data harvester. This harvester is based on workflows, enabling us to add or remove certain steps for different goals of harvesting.\ud \ud The result of our harvesting approach consists of a set of 27,384 POIs, origining from the Dutch Yellow Pages \cite{goudengids2012, and contains an address and a geographical point representation for each POI. These point representations cannot be used to overlay the GPS trajectories directly, and therefore need to be converted into a polygon before providing useful input for the annotation process.\ud \ud Several different approaches to this problem can be thought of, including Voronoi diagrams, nearest-neighbors, and geocoding the addresses of the assumed neighbors. For each of the POI footprint size estimation approaches, the output consists of two parts: 1) a polygon representing the estimated parcel, and 2) an uncertainty function based on the distance to the center of the polygon. These approaches are being validated with cadastral data for the region of Enschede, The Netherlands, and the result of the best approach is used as the input for the GPS trajectory enrichment.\ud \ud The other type of input for the enrichment process is GPS trajectories. This data is generally not smooth, containing outliers, and interruptions of the data stream. Analyzing these imperfections however, may provide valuable information on users entering a rural area, or buildings, respectively.\ud \ud Combining the results of the footprint size estimation with the analyzed GPS trajectory then provides us with uncertain annotated GPS traces

A skeleton design theory for spatial data infrastructure:methodical construction of SDI nodes and SDI networks

In this paper, we look into the theory of designing geoservice systems, i.e., SDI networks and their constituent SDI nodes. As the field of SDI is strongly about bridging between geoservice systems, interoperability and harmonisation, it is not surprising that standardisation efforts are of crucial importance in it. These efforts have historically addressed abstract and concrete content models for data and metadata exchange, as well as abstract and concrete behavioural models for computational processes. The list of standards that are in use in the SDI field continues to expand, and reaches out to neighbouring fields such as sensor nets. We argue that given these trends, the resulting levels of standardisation in actual systems, and the complexity of geoservice systems in general, it appears only natural to look into the possibility to define a standardised design theory for SDI and its nodes, which addresses the function base and the communication base. Specifically, we provide an overview of those components that need to be designed, and what are their relationships. We do so in an abstract way, focussing on the concern of information content in this paper, and only hinting at an appropriate theory of realisation based on our skeleton theory

Automated semantic trajectory annotation with indoor point-of-interest visits in urban areas

User trajectories contain a wealth of implicit information. The places that people visit, provide us with information about their preferences and needs. Furthermore, it provides us with information about the popularity of places, for example at which time of the year or day these places are frequently visited. The potential for behavioral analysis of trajectories is widely discussed in literature, but all of these methods need a pre-processing step: the geometric trajectory data needs to be transformed into a semantic collection or sequence of visited points-of-interest that is more suitable for data mining. Especially indoor activities in urban areas are challenging to detect from raw trajectory data. In this paper, we propose a new algorithm for the automated detection of visited points-of-interest. This algorithm extracts the actual visited points-of-interest well, both in terms of precision and recall, even for the challenging urban indoor activity detection. We demonstrate the strength of the algorithm by comparing it to three existing and widely used algorithms, using annotated trajectory data, collected through an experiment with students in the city of Hengelo, The Netherlands. Our algorithm, which combines multiple trajectory pre-processing techniques from existing work with several novel ones, shows significant improvements