Incremental modelling of ambiguous geometric ideas (I-MAGI): representation and maintenance of vague geometry

During conceptual design, a designer may wish to describe a shape vaguely, either because it is desired that the shape remains flexible or the shape has not yet been defined precisely. Maintaining the vagueness of an early idea until it is sufficiently developed is often of vital importance. However, most existing systems, mainly due to limitations in their modelling capabilities, attempt to interpret and thereby remove the vagueness at the earliest opportunity. This may lead to the loss of considerable information in original concepts or design fixation too early in the design stage. A new approach is needed to represent and maintain vague geometric information and such an approach is presented in this paper.     

不确定移动对象的模糊时空范围查询

指出不确定性和模糊性在时空语义上的区别;提出不确定移动对象的模糊时空范围查询问题,即查询条件中时间、空间范围的外延是模糊的,无清晰的边界,而目标对象的位置不确定;用模糊集表示模糊查询条件,概率密度函数表示移动对象在各自不确定区域内的可能位置分布;给出了不确定对象关于模糊查询条件匹配度的计算方法;设计了基于α截集的无效对象排除和有效对象确认规则及查询算法.算法规则适用于任意概率密度分布.现有的确定或不确定范围查询可以看成是模糊时空范围查询的特例.通过实验验证了算法的效率,在各种参数设置下,约有30%~90%的查询结果可在不计算匹配度的情况下获得.     

VASA: An algebra for vague spatial data in databases

Many geographical applications deal with objects in space that cannot be adequately described by determinate, crisp spatial concepts because of their intrinsically indeterminate and vague nature. Geographical information systems and spatial database systems are currently unable to cope with this kind of data. To support the efficient representation, querying, and manipulation of vague spatial data in a database context, we present a formal data model called vague spatial algebra (VASA). This algebra comprises a set of vague spatial data types for vague points, vague lines, and vague regions together with a comprehensive collection of vague spatial operations and vague topological predicates. One of VASA's main benefits is that its formal framework is based on well known, general, and exact models of crisp spatial data types. This enables an exact definition of the vague spatial model since we can build upon an already existing theory of spatial data types. In particular, crisp spatial data types turn out to be a special case of their vague counterparts. In addition, our approach enables executable specifications for the operations, which can be immediately used as implementations. The article offers a precise and conceptually clean foundation for implementing a DBMS extension for vague spatial data and demonstrates the embedding of these new data types as attribute data types in a database schema as well as the incorporation of vague spatial operations and predicates into queries formulated in an SQL-like query language. All concepts have been verified in a prototype implementation.     

OCL for formal modelling of topological constraints involving regions with broad boundaries

Integrity constraints can control topological relations of objects in spatial databases. These constraints can be modelled using formal languages such as the spatial extension of the Object Constraint Language (Spatial OCL). This language allows the expression of topological integrity constraints involving crisp spatial objects but it does not support constraints involving spatial objects with vague shapes (e.g. forest stand, pollution zone, valley or lake). In this paper, we propose an extension of Spatial OCL based on (1) a geometric model for objects with vague shapes, and (2) an adverbial approach for modelling topological constraints involving regions with broad boundaries. This new language provides an easiness in the formal modelling of these complex constraints. Our approach has been implemented in a code generator. A case study is also presented in the paper in the field of agriculture spreading activities. AOCL _OVS takes account of the shape vagueness of spread parcel and improve spatial reasoning about them.     

Extending the UML concepts to transform natural language queries with fuzzy semantics into SQL

Database applications tend toward getting more versatile and broader to comply with the expansion of various organizations. However, naïve users usually suffer from accessing data arbitrarily by using formal query languages. Therefore, we believe that accessing databases using natural language constructs will become a popular interface in the future. The concept of object-oriented modeling makes the real world to be well represented or expressed in some kinds of logical form. Since the class diagram in UML is used to model the static relationships of databases, in this paper, we intend to study how to extend the UML class diagram representations to capture natural language queries with fuzzy semantics. By referring to the conceptual schema throughout the class diagram representation, we propose a methodology to map natural language constructs into the corresponding class diagram and employ Structured Object Model (SOM) methodology to transform the natural language queries into SQL statements for query executions. Moreover, our approach can handle queries containing vague terms specified in fuzzy modifiers, like ‘good’ or ‘bad’. By our approach, users obtain not only the query answers but also the corresponding degree of vagueness, which can be regarded as the same way we are thinking.     

A cost model for spatio-temporal queries using the TPR-tree

A query optimizer requires cost models to calculate the costs of various access plans for a query. An effective method to estimate the number of disk (or page) accesses for spatio-temporal queries has not yet been proposed. The TPR-tree is an efficient index that supports spatio-temporal queries for moving objects. Existing cost models for the spatial index such as the R-tree do not accurately estimate the number of disk accesses for spatio-temporal queries using the TPR-tree, because they do not consider the future locations of moving objects, which change continuously as time passes.In this paper, we propose an efficient cost model for spatio-temporal queries to solve this problem. We present analytical formulas which accurately calculate the number of disk accesses for spatio-temporal queries. Extensive experimental results show that our proposed method accurately estimates the number of disk accesses over various queries to spatio-temporal data combining real-life spatial data and synthetic temporal data. To evaluate the effectiveness of our method, we compared our spatio-temporal cost model (STCM) with an existing spatial cost model (SCM). The application of the existing SCM has the average error ratio from 52% to 93%, whereas our STCM has the average error ratio from 11% to 32%.     

Augmenting a conceptual model with geospatiotemporal annotations

While many real-world applications need to organize data based on space (e.g., geology, geomarketing, environmental modeling) and/or time (e.g., accounting, inventory management, personnel management), existing conventional conceptual models do not provide a straightforward mechanism to explicitly capture the associated spatial and temporal semantics. As a result, it is left to database designers to discover, design, and implement - on an ad hoc basis - the temporal and spatial concepts that they need. We propose an annotation-based approach that allows a database designer to focus first on nontemporal and nongeospatial aspects (i.e., "what") of the application and, subsequently, augment the conceptual schema with geospatiotemporal annotations (i.e., "when" and "where"). Via annotations, we enable a supplementary level of abstraction that succinctly encapsulates the geospatiotemporal data semantics and naturally extends the semantics of a conventional conceptual model. An overarching assumption in conceptual modeling has always been that expressiveness and formality need to be balanced with simplicity. We posit that our formally defined annotation-based approach is net only expressive, but also straightforward to understand and implement.     

A generic data model for moving objects

Moving objects databases should be able to manage trips that pass through several real world environments, e.g., road network, indoor. However, the current data models only deal with the movement in one situation and cannot represent comprehensive trips for humans who can move inside a building, walk on the pavement, drive on the road, take the public vehicles (bus or train), etc. As a result, existing queries are solely limited to one environment. In this paper, we design a data model that is able to represent moving objects in multiple environments in order to support novel queries on trips in different surroundings and various transportation modes (e.g., Car, Walk, Bus). A generic and precise location representation is proposed that can apply in all environments. The idea is to let the space for moving objects be covered by a set of so-called infrastructures each of which corresponds to an environment and defines the available places for moving objects. Then, the location is represented by referencing to the infrastructure. We formulate the concept of space and infrastructure and propose the methodology to represent moving objects in different environments with the integration of precise transportation modes. Due to different infrastructure characteristics, a set of novel data types is defined to represent infrastructure components. To efficiently support new queries, we design a group of operators to access the data. We present how such a data model is implemented in a database system and report the experimental results. The new model is designed with attention to the data models of previous work for free space and road networks to have a consistent type system and framework of operators. In this way, a powerful set of generic query operations is available for querying, together with those dealing with infrastructures and transportation modes. We demonstrate these capabilities by formulating a set of sophisticated queries across all infrastructures.     

The Influence of the Level of Abstraction on the Evolvability of Conceptual Models of Information Systems

In today's dynamic environments, evolvability of information systems is an increasingly important characteristic. We investigate evolvability at the analysis level, i.e. at the level of the conceptual models that are built of information systems (e.g. UML models). More specifically, we focus on the influence of the level of abstraction of the conceptual model on the evolvability of the model. Abstraction or genericity is a fundamental principle in several research areas such as reuse, patterns, software architectures and application frameworks. The literature contains numerous but vague claims that software based on abstract conceptual models has evolvability advantages. Hypotheses were tested with regard to whether the level of abstraction influences the time needed to apply a change, the correctness of the change and the structure degradation incurred. Two controlled experiments were conducted with 136 subjects. Correctness and structure degradation were rated by human experts. Results indicate that, for some types of change, abstract models are better evolvable than concrete ones. Our results provide insight into how the rather vague claims in literature should be interpreted.     

Direction relations and two-dimensional range queries: optimisation techniques

This paper defines direction relations (e.g., north, northeast) between two-dimensional objects and shows how they can be efficiently retrieved using B-, KDB- and R- tree-based data structures. Essentially, our work studies optimisation techniques for 2D range queries that arise during the processing of direction relations. We test the efficiency of alternative indexing methods through extensive experimentation and present analytical models that estimate their performance. The analytical estimates are shown to be very close to the actual results and can be used by spatial query optimizers in order to predict the retrieval cost. In addition, we implement modifications of the existing structures that yield better performance for certain queries. We conclude the paper by discussing the most suitable method depending on the type of the range and the properties of the data.     

Higher Order Vagueness in Geographical Information: Empirical Geographical Population of Type n Fuzzy Sets

Fuzzy set theory has been suggested as a means for representing vague spatial phenomena, and is widely known for directly addressing some of the issues of vagueness such as the sorites paradox. Higher order vagueness is widely considered a necessary component of any theory of vagueness, but it is not so well known that it too is competently modelled by Type n Fuzzy sets. In this paper we explore the fuzzy representation of higher order vagueness with respect to spatial phenomena. Initially we relate the arguments on philosophical vagueness to Type n Fuzzy sets. As an example, we move on to an empirical generation of spatial Type 2 Fuzzy sets examining the spatial extent of mountain peaks in Scotland. We show that the Type 2 Fuzzy sets can be populated by using alternative parameterisations of a peak detection algorithm. Further ambiguities could also be explored using other parameters of this and other algorithms. We show some novel answers to interrogations of the mountain peaks of Scotland. The conclusion of this work is that higher order vagueness can be populated for Type 2 and higher fuzzy sets. It does not follow that it is always necessary to examine these higher order uncertainties, but a possible advantage in terms of the results of spatial inquiry is demonstrated.

A data model and query language for spatio-temporal decision support

In recent years, applications aimed at exploring and analyzing spatial data have emerged, powered by the increasing need of software that integrates Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP). These applications have been called SOLAP (Spatial OLAP). In previous work, the authors have introduced Piet, a system based on a formal data model that integrates in a single framework GIS, OLAP (On-Line Analytical Processing), and Moving Object data. Real-world problems are inherently spatio-temporal. Thus, in this paper we present a data model that extends Piet, allowing tracking the history of spatial data in the GIS layers. We present a formal study of the two typical ways of introducing time into Piet: timestamping the thematic layers in the GIS, and timestamping the spatial objects in each layer. We denote these strategies snapshot-based and timestamp-based representations, respectively, following well-known terminology borrowed from temporal databases. We present and discuss the formal model for both alternatives. Based on the timestamp-based representation, we introduce a formal First-Order spatio-temporal query language, which we denote L_t,\mathcal{L}_t, able to express spatio-temporal queries over GIS, OLAP, and trajectory data. Finally, we discuss implementation issues, the update operators that must be supported by the model, and sketch a temporal extension to Piet-QL, the SQL-like query language that supports Piet.     

Enriching the conceptual basis for query formulation through relationship semantics in databases

The rapid increase in end-user computing calls into question the suitability of existing database query languages (DBQLs). Because the typical DB end-user is not a DB specialist, it is essential that DBQLs use concepts that are as close as possible to those in the end-users’ cognitive mental model and adopt interface techniques that are suited to end-users’ abilities. Concept-based query languages are well suited for this. This realization has motivated further research in conceptual, or semantic, query approaches. However, the primary focus in this field has been on semantic query optimization, not on query formulation. In this study, we address ourselves to the problem of formulation of queries using concepts. We propose a concept-based query language, called the conceptual query language (CQL), which allows for the conceptual abstraction of database queries and exploits the rich semantics of data models to ease and facilitate query formulation.The CQL approach uses the relationship semantics of semantic data models to render transparent the technical complexities of existing DB query languages. Association semantics are also used to automatically construct query graphs and pseudo-natural language explanations of queries, and to generate SQL codes. A set theoretic formalism for conceptual queries is developed and used. This paper discusses the design of CQL, its expressive power, its implementation, and the strategies for CQL query processing. The implementation of a CQL prototype is briefly discussed in this paper. User experiments were carried out extensively and showed the advantage of CQL over alternative languages such as SQL.     

Approximation-Based Similarity Search for 3-D Surface Segments

The issue of finding similar 3-D surface segments arises in many recent applications of spatial database systems, such as molecular biology, medical imaging, CAD, and geographic information systems. Surface segments being similar in shape to a given query segment are to be retrieved from the database. The two main questions are how to define shape similarity and how to efficiently execute similarity search queries. We propose a new similarity model based on shape approximation by multi-parametric surface functions that are adaptable to specific application domains. We then define shape similarity of two 3-D surface segments in terms of their mutual approximation errors. Applying the multi-step query processing paradigm, we propose algorithms to efficiently support complex similarity search queries in large spatial databases. A new query type, called the ellipsoid query, is utilized in the filter step. Ellipsoid queries, being specified by quadratic forms, represent a general concept for similarity search. Our major contribution is the introduction of efficient algorithms to perform ellipsoid queries on multidimensional index structures. Experimental results on a large 3-D protein database containing 94,000 surface segments demonstrate the successful application and the high performance of our method.     

Vagueness and Rough Location

This paper deals with the representation and the processing of information about spatial objects with indeterminate location like valleys or dunes (objects subject to vagueness). The indeterminacy of the location of spatial objects is caused by the vagueness of the unity condition provided by the underlying human concepts valley and dune. We propose the notion of rough, i.e., approximate, location for representing and processing information about indeterminate location of objects subject to vagueness. We provide an analysis of the relationships between vagueness of concepts, indeterminacy of location of objects, and rough approximations using methods of formal ontology. In the second part of the paper we propose an algebraic formalization of rough location, and hence, a formal method for the representation of objects subject to vagueness on a computer. We further define operations on those representations, which can be interpreted as union and intersection operations between those objects. The discussion of vagueness of concepts, indeterminacy of location, rough location and the relationships between these notions contributes to the theory about the ontology of geographic space. The formalization presented can provide the foundation for the implementation of vague objects and their location indeterminacy in GIS.     

A content-search information retrieval process based on conceptual graphs

An intelligent information retrieval system is presented in this paper. In our approach, which complies with the logical view of information retrieval, queries, document contents and other knowledge are represented by expressions in a knowledge representation language based on the conceptual graphs introduced by Sowa. In order to take the intrinsic vagueness of information retrieval into account, i.e. to search documents imprecisely and incompletely represented in order to answer a vague query, different kinds of probabilistic logic are often used. The search process described in this paper uses graph transformations instead of probabilistic notions. This paper is focused on the content-based retrieval process, and the cognitive facet of information retrieval is not directly addressed. However, our approach, involving the use of a knowledge representation language for representing data and a search process based on a combinatorial implementation of van Rijsbergen’s logical uncertainty principle, also allows the representation of retrieval situations. Hence, we believe that it could be implemented at the core of an operational information retrieval system. Two applications, one dealing with academic libraries and the other concerning audiovisual documents, are briefly presented.     

Fuzzy approach to the intelligent management of virtual spaces.

This paper presents research carried out toward the improvement of current virtual environments from an intelligent systems approach. A novel architecture to solve vague queries that allows users to find objects and scenes in virtual environments is described. As a base, a new virtual worlds representation model and an associated fuzzy querying approach are used. The new representation model adds a semantic level to the usual models, providing more suitable environments for the interaction with users. The query solver is able to work with queries expressing the vagueness inherent to human conceptualization of visual perception (for example, tall tree, a park with many tall trees, or a park bench near approximately five tall trees). The system has been developed and evaluated with user experiments, where comparison with navigation and keyword-based query approaches have been realized. The results of this study show that the proposed architecture is more powerful and intuitive for finding the targets.     

Spatio-temporal composition and indexing for large multimedia applications

Multimedia applications usually involve a large number of multimedia objects (texts, images, sounds, etc.). An important issue in this context is the specification of spatial and temporal relationships among these objects. In this paper we define such a model, based on a set of spatial and temporal relationships between objects participating in multimedia applications. Our work exploits existing approaches for spatial and temporal relationships. We extend these relationships in order to cover the specific requirements of multimedia applications and we integrate the results in a uniform framework for spatio-temporal composition representation. Another issue is the efficient handling of queries related to the spatio-temporal relationships among the objects during the authoring process. Such queries may be very costly and appropriate indexing schemes are needed so as to handle them efficiently. We propose efficient such schemes, based on multidimensional (spatial) data structures, for large multimedia applications that involve thousands of objects. Evaluation models of the proposed schemes are also presented, as well as hints for the selection of the most appropriate one, according to the multimedia author's requirements.     

Differentially private counting of users’ spatial regions

Mining of spatial data is an enabling technology for mobile services, Internet-connected cars and the Internet of Things. But the very distinctiveness of spatial data that drives utility can cost user privacy. Past work has focused upon points and trajectories for differentially private release. In this work, we continue the tradition of privacy-preserving spatial analytics, focusing not on point or path data, but on planar spatial regions. Such data represent the area of a user’s most frequent visitation—such as “around home and nearby shops”. Specifically we consider the differentially private release of data structures that support range queries for counting users’ spatial regions. Counting planar regions leads to unique challenges not faced in existing work. A user’s spatial region that straddles multiple data structure cells can lead to duplicate counting at query time. We provably avoid this pitfall by leveraging the Euler characteristic for the first time with differential privacy. To address the increased sensitivity of range queries to spatial region data, we calibrate privacy-preserving noise using bounded user region size and a constrained inference that uses robust least absolute deviations. Our novel constrained inference reduces noise and promotes covertness by (privately) imposing consistency. We provide a full end-to-end theoretical analysis of both differential privacy and high-probability utility for our approach using concentration bounds. A comprehensive experimental study on several real-world datasets establishes practical validity.     

Partially materialized digest scheme: an efficient verification method for outsourced databases

In the outsourced database model, a data owner publishes her database through a third-party server; i.e., the server hosts the data and answers user queries on behalf of the owner. Since the server may not be trusted, or may be compromised, users need a means to verify that answers received are both authentic and complete, i.e., that the returned data have not been tampered with, and that no qualifying results have been omitted. We propose a result verification approach for one-dimensional queries, called Partially Materialized Digest scheme (PMD), that applies to both static and dynamic databases. PMD uses separate indexes for the data and for their associated verification information, and only partially materializes the latter. In contrast with previous work, PMD avoids unnecessary costs when processing queries that do not request verification, achieving the performance of an ordinary index (e.g., a B⁺-tree). On the other hand, when an authenticity and completeness proof is required, PMD outperforms the existing state-of-the-art technique by a wide margin, as we demonstrate analytically and experimentally. Furthermore, we design two verification methods for spatial queries. The first, termed Merkle R-tree (MR-tree), extends the conventional approach of embedding authentication information into the data index (i.e., an R-tree). The second, called Partially Materialized KD-tree (PMKD), follows the PMD paradigm using separate data and verification indexes. An empirical evaluation with real data shows that the PMD methodology is superior to the traditional approach for spatial queries too.