Showing papers by "Christian S. Jensen published in 2003"

Nearest neighbor queries in road networks

Abstract: With wireless communications and geo-positioning being widely available, it becomes possible to offer new e-services that provide mobile users with information about other mobile objects. This paper concerns active, ordered k-nearest neighbor queries for query and data objects that are moving in road networks. Such queries may be of use in many services.Specifically, we present an easily implementable data model that serves well as a foundation for such queries. We also present the design of a prototype system that implements the queries based on the data model. The algorithm used for the nearest neighbor search in the prototype is presented in detail. In addition, the paper reports on results from experiments with the prototype system.

Supporting frequent updates in R-trees: a bottom-up approach

Abstract: Advances in hardware-related technologies promise to enable new data management applications that monitor continuous processes. In these applications, enormous amounts of state samples are obtained via sensors and are streamed to a database. Further, updates are very frequent and may exhibit locality. While the R-tree is the index of choice for multi-dimensional data with low dimensionality, and is thus relevant to these applications, R-tree updates are also relatively inefficient. We present a bottom-up update strategy for R-trees that generalizes existing update techniques and aims to improve update performance. It has different levels of reorganization--ranging from global to local--during updates, avoiding expensive top-down updates. A compact main-memory summary structure that allows direct access to the R-tree index nodes is used together with efficient bottom-up algorithms. Empirical studies indicate that the bottom-up strategy outperforms the traditional top-down technique, leads to indices with better query performance, achieves higher throughput, and is scalable.

Spatio-Temporal Databases: The CHOROCHRONOS Approach

Abstract: 1: Introduction.- 2: Ontology for Spatio-temporal Databases.- 3: Conceptual Models for Spatio-temporal Applications.- 4: Spatio-temporal Models and Languages: An Approach Based on Data Types.- 5: Spatio-temporal Models and Languages: An Approach Based on Constraints.- 6: Access Methods and Query Processing Techniques.- 7: Architectures and Implementations of Spatio-temporal Database Management Systems.- 8: Advanced Uses: Composing Interactive Spatio-temporal Documents.- 9: Spatio-temporal Databases in the Years Ahead.

Indexing of network constrained moving objects

Abstract: With the proliferation of mobile computing, the ability to index efficiently the movements of mobile objects becomes important. Objects are typically seen as moving in two-dimensional (x,y) space, which means that their movements across time may be embedded in the three-dimensional (x,y,t) space. Further, the movements are typically represented as trajectories, sequences of connected line segments. In certain cases, movement is restricted, and specifically in this paper, we aim at exploiting that movements occur in transportation networks to reduce the dimensionality of the data. Briefly, the idea is to reduce movements to occur in one spatial dimension. As a consequence, the movement data becomes two-dimensional (x,t). The advantages of considering such lower-dimensional trajectories are the reduced overall size of the data and the lower-dimensional indexing challenge. Since off-the-shelf systems typically do not offer higher-dimensional indexing, this reduction in dimensionality allows us to use such DBMSes to store and index trajectories. Moreover, we argue that, given the right circumstances, indexing these dimensionality-reduced trajectories can be more efficient than using a three-dimensional index. This hypothesis is verified by an experimental study that incorporates trajectories stemming from real and synthetic road networks.

Computational data modeling for network-constrained moving objects

Abstract: Advances in wireless communications, positioning technology, and other hardware technologies combine to enable a range of applications that use a mobile user's geo-spatial data to deliver online, location-enhanced services, often referred to as location-based services. Assuming that the service users are constrained to a transportation network, this paper develops data structures that model road networks, the mobile users, and stationary objects of interest. The proposed framework encompasses two supplementary road network representations, namely a two-dimensional representation and a graph representation. These capture aspects of the problem domain that are required in order to support the querying that underlies the envisioned location-based services.

Integrated data management for mobile services in the real world

Abstract: Market research companies predict a huge market for services to be delivered to mobile users. Services include route guidance, point-of-interest search, metering services such as road pricing and parking payment, traffic monitoring, etc. We believe that no single such service will be the killer service, but that suites of integrated services are called for. Such integrated services reuse integrated content obtained from multiple content providers. This paper describes concepts and techniques underlying the data management system deployed by a Danish mobile content integrator. While georeferencing of content is important, it is even more important to relate content to the transportation infrastructure. The data management system thus relies on several sophisticated, integrated representations of the infrastructure, each of which supports its own kind of use. The paper covers data modeling, querying, and update, as well as the applications using the system.

Chapter 3: Conceptual Models for Spatio-temporal Applications

Abstract: Improved support for modeling information systems involving time-varying, georeferenced information, termed spatio-temporal information, has been a longterm user requirement in a variety of areas, such as cadastral systems that capture the histories of landparcels, routing systems computing possible routes of vehicles, and weather forecasting systems. This chapter concerns the conceptual database design phase for such spatio-temporal information systems and presents two models, namely the spatio-temporal Entity Relationship (ER) Model and the Extended spatio-temporal Unified Modeling Language (UML) as proposed in [33,34] and [26], respectively.

A Foundation for Vacuuming Temporal Databases

Abstract: A wide range of real-world database applications, including financial and medical applications, are faced with accountability and traceability requirements. These requirements lead to the replacement of the usual update-in-place policy by an append-only policy that retain all previous states in the database. This policy result in so-called transaction-time databases which are ever-growing. A variety of physical storage structures and indexing techniques as well as query languages have been proposed for transaction-time databases, but the support for physical removal of data, termed vacuuming, has only received little attention. Such vacuuming is called for by, e.g., the laws of many countries and the policies of many businesses. Although necessary, with vacuuming, the database's perfect recollection of the past may be compromised via, e.g., selective removal of records pertaining to past states. This paper provides a semantic foundation for the vacuuming of transaction-time databases. The main focus is to establish a foundation for the correct processing of queries and updates against vacuumed databases. However, options for user, application, and database interactions in response to queries and updates against vacuumed data are also outlined.

A foundation for vacuuming temporal databases

Abstract: A wide range of real-world database applications, including financial and medical applications, are faced with accountability and traceability requirements. These requirements lead to the replacement of the usual update-in-place policy by an append-only policy that retain all previous states in the database. This policy result in so-called transaction-time databases which are ever-growing. A variety of physical storage structures and indexing techniques as well as query languages have been proposed for transaction-time databases, but the support for physical removal of data, termed vacuuming, has only received little attention. Such vacuuming is called for by, e.g., the laws of many countries and the policies of many businesses. Although necessary, with vacuuming, the database's perfect recollection of the past may be compromised via, e.g., selective removal of records pertaining to past states. This paper provides a semantic foundation for the vacuuming of transaction-time databases. The main focus is to establish a foundation for the correct processing of queries and updates against vacuumed databases. However, options for user, application, and database interactions in response to queries and updates against vacuumed data are also outlined.

4 Spatio-temporal Models and Languages: An Approach Based on Data Types

Abstract: vs. Discrete Modeling. What does it mean to develop a data model with spatio-temporal data types? Actually, this is a design of a many-sorted algebra. There are two steps: 1. Invent a number of types and operations between them that appear to be suitable for querying. So far these are just names, which means one gives a signature. Formally, the signature consists of sorts (names for the types) and operators (names for the operations). 2. Define semantics for this signature, that is, associate an algebra, by defining carrier sets for the sorts and functions for the operators. So the carrier set for a type α contains the possible values for α, and the functions are mappings between the carrier sets. For a formal definition of many-sorted signature and algebra see [24] or [18]. Now one can make such designs at two different levels of abstraction, namely as abstract or as discrete models. Abstract models allow us to make definitions in terms of infinite sets, without worrying whether finite representations of these sets exist. This allows us to view a moving point as a continuous curve in the 3D space, as an arbitrary mapping from an infinite time domain into an also infinite space domain. All the types that we get by application of the type constructor τ are functions over an infinite domain, hence each value is an infinite set. This abstract view is the conceptual model that we are interested in. The curve described by a plane flying over space is continuous; for any point in time there exists a value, regardless of whether we are able to give a finite description for this mapping (or relation). In Section 4.2.2 we have in fact described the types mentioned under this view. In an abstract model, we have no problem in using types like “moving real”, mreal, and operations like mpoint×mpoint → mreal mdistance since it is quite clear that at any time some distance between the moving points exists (when both are defined). 4 Models and Languages: Data Types 105 The only trouble with abstract models is that we cannot store and manipulate them in computers. Only finite and in fact reasonably small sets can be stored; data structures and algorithms have to work with discrete (finite) representations of the infinite point sets. From this point of view, abstract models are entirely unrealistic; only discrete models are usable. This means we somehow need discrete models for moving points and moving regions as well as for all other involved types (mreal, region, . . . ). We can view discrete models as approximations, finite descriptions of the infinite shapes we are interested in. In spatial databases there is the same problem of giving discrete representations for in principle continuous shapes; there almost always linear approximations have been used. Hence, a region is described in terms of polygons and a curve in space (e.g. a river) by a polyline. Linear approximations are attractive because they are easy to handle mathematically; most algorithms in computational geometry work on linear shapes such as rectangles, polyhedra, etc. A linear approximation for a moving point is a polyline in 3D space; a linear approximation for a moving region is a set of polyhedra (see Figure 4.2). Remember that a moving point can be a partial function, hence it may disappear at times, the same is true for the moving region.

Data Modeling for Mobile Services in the Real World

Abstract: Research contributions on data modeling, data structures, query processing, and indexing for mobile services may have an impact in the longer term, but each contribution typically offers an isolated solution to one small part of the practical problem of delivering mobile services in the real world. In contrast, this paper describes holistic concepts and techniques for mobile data modeling that are readily applicable in practice. Focus is on services to be delivered to mobile users, such as route guidance, point-of-interest search, road pricing, parking payment, traffic monitoring, etc. While geo-referencing of content is important, it is even more important to relate content to the transportation infrastructure. In addition, several sophisticated, integrated representations of the infrastructure are needed.

Spatio-temporal Models and Languages: An Approach Based on Data Types.

Abstract: In this chapter we develop DBMS data models and query languages to deal with geometries changing over time. In contrast to most of the earlier work on this subject, these models and languages are capable of handling continuously changing geometries, or moving objects. We focus on two basic abstractions called moving point and moving region. A moving point can represent an entity for which only the position in space is relevant. A moving region captures moving as well as growing or shrinking regions. Examples for moving points are people, polar bears, cars, trains, or air planes; examples for moving regions are hurricanes, forest fires, or oil spills in the sea.

Architectures and implementations of spatio-temporal database management systems

Abstract: This chapter is devoted to architectural and implementation aspects of spatiotemporal database management systems. It starts with a general introduction into architectures and commercial approaches to extending databases by spatiotemporal features. Thereafter, the prototype systems Concert, Secondo, Dedale, Tiger, and GeoToolKit are presented.

Conceptual models for spatio-temporal applications

Abstract: Improved support for modeling information systems involving time-varying, georeferenced information, termed spatio-temporal information, has been a longterm user requirement in a variety of areas, such as cadastral systems that capture the histories of landparcels, routing systems computing possible routes of vehicles, and weather forecasting systems. This chapter concerns the conceptual database design phase for such spatio-temporal information systems and presents two models, namely the spatio-temporal Entity Relationship (ER) Model and the Extended spatio-temporal Unified Modeling Language (UML) as proposed in [33,34] and [26], respectively. The conceptual design phase focuses on expressing application requirements without the use of computer metaphors. The design should be understandable to the user and complete, so that it can be translated into the logical phase that follows without any further user input. Popular conceptual models include the ER model [6], IFO [2], OMT [30], and UML [17]. For conventional administrative systems, exemplified by the “supplier-supplies-parts” paradigm, the available modeling notations and techniques that support the conceptual and logical modeling phases are mature and adequate. However, this is not the case in non-standard systems managing spatio-temporal, multimedia, VLSI, image, and voice data. Rather, these lead to new and unmet requirements for modeling techniques. The basic rationale behind the work presented here is to introduce new modeling techniques, based on minimal extensions of existing models, developed to accommodate the peculiarities of the combined spatial and temporal information. The ER Model and the UML have been extended as prototypical examples for this purpose. First, we present the fundamental aspects of the spatio-temporal domain, covering concepts such as objects, properties, and relationships. Based on these, in the ER approach, we present a small set of constructs aimed at improving the ability to conveniently model spatio-temporal information at the conceptual level. These constructs may be included in a wide range of existing conceptual data models, improving their modeling capabilities without fundamentally changing the models. We incorporate the proposed modeling constructs into the ER model ([5]), resulting in the semantically richer Spatio-Temporal ER (STER) model [33].

Incomplete information in multidimensional databases

Abstract: While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information in base data, derived data, and dimensions. This chapter presents several strategies for managing incomplete information in multidimensional databases. Which strategy to use is dependent on the kind of incomplete information present, and also on where it occurs in the multidimensional database. A relatively simple strategy is to replace incomplete information with appropriate, complete information. The advantage of this strategy is that all multidimensional databases can manage complete information. Other strategies require more substantial changes to the multidimensional database. One strategy is to reflect the incompleteness in computed aggregates, which is possible only if the multidimensional database allows incomplete values in its hierarchies. Another strategy is to measure the amount of incompleteness in aggregated values by tallying how much uncertain information went into their production.

Object-relational management of multiply represented geographic entities

Abstract: Multiple representations occur when information about the same geographic entity is represented electronically more than once. This occurs frequently in practice, and it invariably results in the occurrence of inconsistencies among the different representations. We propose to resolve this situation by introducing a multiple representation management system (MRMS), the schema of which includes rules that specify how to identify representations of the same entity, rules that specify consistency requirements, and rules used to restore consistency when necessary. In this paper, we demonstrate by means of a prototype and a real-world case study that it is possible to implement a multiple representation schema language on top of an object-relational database management system. Specifically, it is demonstrated how it is possible to map the constructs of the language used for specifying the multiple representation schema to functionality available in Oracle. Though some limitations exist, Oracle has proven to be a suitable platform for implementing an MRMS.

Extending UML for space- and time-dependent applications

Abstract: INTRODUCTION In recent years, the need for a temporal dimension in traditional spatial information systems and for high-level models useful for the conceptual design of the resulting spatiotemporal systems has become clear. Although having in common a need to manage spatial data and their changes over time, various spatiotemporal applications may manage different types of spatiotemporal data and may be based on very different models of space, time, and change. For example, the term spatiotemporal data is used to refer both to temporal changes in spatial extents, such as redrawing the boundaries of a voting precinct or land deed, and to changes in the value of thematic (i.e., alphanumeric) data across time or space, such as variation in soil acidity measurements depending on the measurement location and date. A spatiotemporal application may be concerned with either or both types of data. This, in turn, is likely to influence the underlying model of space employed, e.g., the two types of spatiotemporal data generally correspond to an objectversus a field-based spatial model. For either type of spatiotemporal data, change may occur in discrete steps, e.g., changes in land deed boundaries, or in a continuous process, e.g., changes in the position of a moving object such as a car. Another type of spatiotemp ral data is composite data whose components vary depending on time or location. An example is the minimum combination of equipment and wards required in a certain category of hospital (e.g., general, maternity, psychiatric), where the relevant regulations determining the applicable base standards vary by locality and time period.

Chapter 4: Spatio-temporal Models and Languages: An Approach Based on Data Types

Abstract: In this chapter we develop DBMS data models and query languages to deal with geometries changing over time. In contrast to most of the earlier work on this subject, these models and languages are capable of handling continuously changing geometries, or moving objects. We focus on two basic abstractions called moving point and moving region. A moving point can represent an entity for which only the position in space is relevant. A moving region captures moving as well as growing or shrinking regions. Examples for moving points are people, polar bears, cars, trains, or air planes; examples for moving regions are hurricanes, forest fires, or oil spills in the sea.

Chapter 6: Access Methods and Query Processing Techniques

Abstract: The performance of a database management system (DBMS) is fundamentally dependent on the access methods and query processing techniques available to the system. Traditionally, relational DBMSs have relied on well-known access methods, such as the ubiquitous B + -tree, hashing with chaining, and, in some cases, linear hashing [52]. Object-oriented and object-relational systems have also adopted these structures to a great extend.

Modeling and Testing Legacy Data Consistency Requirements

Abstract: An increasing number of data sources are available on the Internet, many of which offer semantically overlapping data, but based on different schemas, or models. While it is often of interest to integrate such data sources, the lack of consistency among them makes this integration difficult.

Towards a Data Consistency Modeling and Testing Framework for MOF Defined Languages

Abstract: The number of online data sources is continuously increasing, and related data are often available from several sources. However accessing data from multiple sources is hindered by the use of different languages and schemas at the sources, as well as by inconsistencies among the data. There is thus a growing need for tools that enable the testing of consistency among data from different sources. This paper puts forward the concept of a framework, that supports the integration of UML models and ontologies written in languages such as the W3C Web Ontology Language (OWL). The framework will be based on the Meta Object Facility (MOF); a MOF metamodel (e.g. a metamodel for OWL) can be input as a specification, the framework will then allow the user to instantiate the specified metamodel. Consistencies requirements are specified using a special modeling technique that is characterized by its use of special Boolean class attributes, termed consistency attributes, to which OCL expressions are attached. The framework makes it possible to exercise the modeling technique on two or more legacy models and in this way specify consistency between models. Output of the consistency modeling is called an integration model which consist of the legacy models and the consistency model. The resulting integration model enables the testing of consistency between instances of legacy models; the consistency model is automatically instantiated and the consistency attribute values that are false indicates inconsistencies.

Spatio-Temporal Data Exchange Standards

Abstract: We believe that research that concerns aspects of spatio-temporal data management may benefit from taking into account the various standards for spatio-temporal data formats. For example, this may contribute to rendering prototype software “open” and more readily useful. This paper thus identifies and briefly surveys standardization in relation to primarily the exchange and integration of spatio-temporal data. An overview of several data exchange languages is offered, along with reviews their potential for facilitating the collection of test data and the leveraging of prototypes. The standards, most of which are XML-based, lend themselves to the integration of prototypes into middleware architectures, e.g., as Web services.