Conjunctive Visual Forms

Visual exploration of multidimensional data is a process of isolating and extracting relationships within and between dimensions. Coordinated multiple view approaches are particularly effective for visual exploration because they support precise expression of heterogeneous multidimensional queries using simple interactions. Recent visual analytics research has made significant progress in identifying and understanding patterns of composed views and coordinations that support fast, flexible, and open-ended data exploration. What is missing is formalization of the space of expressible queries in terms of visual representation and interaction. This paper introduces the conjunctive visual form model in which visual exploration consists of interactively-driven sequences of transitions between visual states that correspond to conjunctive normal forms in boolean logic. The model predicts several new and useful ways to extend the space of rapidly expressible queries through addition of simple interactive capabilities to existing compositional patterns. Two recent related visual tools offer a subset of these capabilities, providing a basis for conjecturing about such extensions.     

A graph-based framework for multiparadigmatic visual access todatabases

Describes an approach for multiparadigmatic visual access integration of different interaction paradigms. The user is provided with an adaptive interface augmented by a user model, supporting different visual representations of both data and queries. The visual representations are characterized on the basis of the chosen visual formalisms, namely forms, diagrams and icons. To access different databases, a unified data model called the “graph model” is used as a common underlying formalism to which databases, expressed in the most popular data models, can be mapped. Graph model databases are queried through the adaptive interface. The semantics of the query operations is formally defined in terms of graphical primitives. Such a formal approach permits us to define the concept of an “atomic query”, which is the minimal portion of a query that can be transferred from one interaction paradigm to another and processed by the system. Since certain interaction modalities and visual representations are more suitable for certain user classes, the system can suggest to the user the most appropriate interaction modality as well as the visual representation, according to the user model. Some results on user model construction are presented     

QBD*: a graphical query language with recursion

A system to query databases using diagrams as a standard user interface is proposed. The system, called Query by Diagram* (QBD*), makes use of a conceptual data model, a query language on this model, and a graphical user interface. The conceptual model is the entity-relationship model. The query language, whose expressive power allows recursive queries, supports visual interaction. The main characteristics of the interface are ease of use and the availability of a rich set of primitives for schema selection and query formulation. The expressive power of QBD* and G⁺, which are the only languages allowing recursive queries to be expressed graphically are compared     

SEE: a Spatial Exploration Environment based on adirect-manipulation paradigm

The need to provide effective tools for analyzing and querying spatial data is becoming increasingly important with the explosion of data in applications such as geographic information systems, image databases, CAD, and remote sensing. The SEE (Spatial Exploration Environment) is the first effort at applying direct-manipulation visual information seeking (VIS) techniques to spatial data analysis by visually querying as well as browsing spatial data and reviewing the visual results for trend analysis. The SEE system incorporates a visual query language (SVIQUEL) that allows users to specify the relative spatial position (both topology and direction) between objects using direct manipulation. The quantitative SVIQVEL sliders (S-sliders) are complemented by the qualitative active-picture-for-querying (APIQ) interface that allows the user to specify qualitative relative position queries. APIQ provides qualitative visual representations of the quantitative query specified by the S-sliders. This increases the utility of the system for spatial browsing and spatial trend discovery with no particular query in mind. The SVIQUEL queries are processed using a k-Bucket index structure specifically tuned for incremental processing of the multidimensional range queries that represent the class of queries that can be expressed by SVIQUEL. We have also designed a tightly integrated map visualization that helps to preserve the spatial context and a bar visualization that provides a qualitative abstraction of aggregates     

A shape-based visual interface for text retrieval

We describe a shape-based visual interface for information retrieval and interactive exploration that exploits shape recognition. Our exploratory system uses procedurally generated shapes coupled with an underlying text-retrieval engine. A visual interface based on 3D shapes (glyphs) enhances traditional text-based queries and summarization. Our interface lets users visualize multidimensional relationships among documents and perceive more information than with conventional text-based interfaces. It promotes information overview and drill-down in support of analysis. Before describing our visual interface and application, we introduce information retrieval within the context of data mining and provide a brief overview of procedural shape generation. We then describe our current system and give a few relevant examples. Finally, we offer some ideas for future enhancements and direction     

Visual spatio-temporal function-based querying

Visual interfaces are very important for human interactions in cyberworlds. Visual spatio-temporal querying should be one of the basic tools for data mining and retrieval in cyberworlds. In this paper, we propose a novel function-based query model for arbitrary shape spatio-temporal querying. The queries are defined as geometric shapes changing over time. In our model, data are interpreted geometrically as multidimensional points with time dimension or as moving points. The queries are formulated with geometric objects and operations over them to form the query solid changing over time. The proposed query model allows us to pose arbitrary shape spatio-temporal range queries. With the uniform geometric model we integrate visual mining and querying of time-dependent data employing 3D visualization tools. It allows for creating an intuitive visual interface using 2D projections of 3D query shapes. Our approach combines visualization of spatio-temporal data with visualization of the range query formulation employing very compact function-based query model. The implemented visual query system and its visual interface are proposed and described. An example of application of the system in analysis of simulation results in molecular dynamics is considered.     

Rolling the dice: multidimensional visual exploration using scatterplot matrix navigation

Scatterplots remain one of the most popular and widely-used visual representations for multidimensional data due to their simplicity, familiarity and visual clarity, even if they lack some of the flexibility and visual expressiveness of newer multidimensional visualization techniques. This paper presents new interactive methods to explore multidimensional data using scatterplots. This exploration is performed using a matrix of scatterplots that gives an overview of the possible configurations, thumbnails of the scatterplots, and support for interactive navigation in the multidimensional space. Transitions between scatterplots are performed as animated rotations in 3D space, somewhat akin to rolling dice. Users can iteratively build queries using bounding volumes in the dataset, sculpting the query from different viewpoints to become more and more refined. Furthermore, the dimensions in the navigation space can be reordered, manually or automatically, to highlight salient correlations and differences among them. An example scenario presents the interaction techniques supporting smooth and effortless visual exploration of multidimensional datasets.     

Formalizing visual interaction with historical databases

Recent database applications are typically oriented towards a large set of non-expert users, and therefore, they need to be equipped with suitable interfaces facilitating the interaction with the system. Moreover, the incorporation of the time dimension in database systems is a desirable feature. Indeed, several temporal data models and the corresponding textual query languages have been proposed. However, there is a limited amount of research concerning the investigation of user-oriented languages for querying temporal databases. Our proposal addresses such a need. In particular, we propose a visual query environment, namely Temporal Visual Query Environment (TVQE) which provides an easier interaction of the user with temporal databases. The system adopts a diagrammatic representation of the database schema (including temporal classes and relationships) and a “graphical notebook” as interaction metaphor. In our approach, non-database experts are released from syntactical difficulties which are typical of textual languages, and they can easily express temporal queries by means of elementary graphical operations (e.g. click on a node label). Differently from many proposals in the field of visual query languages, the language underlying TVQE is provided with formal syntax and semantics. It is based on a minimal set of temporal graphical primitives (TGPs), which are defined on a Temporal Graph Model (TGM), with visual syntax and object-based semantics. In this paper we mainly concentrate on the formal aspects of TVQE, and provide some hints on the visual interaction mechanisms and implementation issues.     

A graphical query language: VISUAL and its query processing

This paper describes VISUAL, a graphical icon-based query language with a user-friendly graphical user interface for scientific databases and its query processing techniques. VISUAL is suitable for domains where visualization of the relationships is important for the domain scientist to express queries. In VISUAL, graphical objects are not tied to the underlying formalism; instead, they represent the relationships of the application domain. VISUAL supports relational, nested, and object-oriented models naturally and has formal basis. For ease of understanding and for efficiency reasons, two VISUAL semantics are introduced, namely, the interpretation and execution semantics. Translations from VISUAL to the Object Query Language (for portability considerations) and to an object algebra (for query processing purposes) are presented. Concepts of external and internal queries are developed as modularization tools.     

A visual query language for graphical interaction withschema-intensive databases

This paper presents a visual query language called VQL for interacting with an object-oriented schema-intensive data model. VQL allows convenient access to the various types of knowledge captured by the semantic model. It consists of a set of “graphical primitives” along with a combination grammar for creating graphical queries. The visual language is internally supported by a prolog-like predicate based query language. The formal grammar underlying the predicate based language is also presented. Apart from being able to create simple queries that can be specified in SQL or QBE, VQL can be used for making queries on any object-oriented data model including the generalization of the E-R model. VQL also handles complicated, indirect queries, specially those that require a reasoning system for query interpretation and response generation. Further, recursive queries on graph structures such as finding transitive closures of graphs may be easily specified. Perhaps the most powerful feature of VQL is its ability to provide high semantic expressibility (in being able to specify highly complex queries) while maintaining simplicity in the user's query formulation process. VQL is embedded in an object-oriented graphical database interaction environment that supports schema creation and manipulation in addition to database querying and updation. The prototype has been implemented in Smalltalk-80 running on a Sun 3/60 workstation. All the illustrations of visual interaction presented are taken from actual interaction sessions     

Graphics by a Logic Database Management System

The GEDBLOG system allows applications which manipulate graphic objects to be developed following a declarative definitional style. GEDBLOG supports the consistent design and prototyping of graphic applications through an incremental development and makes it possible to guarantee automatically that the application meets its specifications. Typical GEDBLOG applications have graphics as their characterizing element and can be found, for example, in the CAD/CAM, visual languages or graphical interface areas. The system is obtained by integrating a graphical data language in an existing logic database management system, EDBLOG, so that graphic and non-graphic information is handled in a uniform declarative way.     

Using visual spatial search interface for WWW applications

Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented.     

Lyra: An Interactive Visualization Design Environment

We present Lyra, an interactive environment for designing customized visualizations without writing code. Using drag‐and‐drop interactions, designers can bind data to the properties of graphical marks to author expressive visualization designs. Marks can be moved, rotated and resized using handles; relatively positioned using connectors; and parameterized by data fields using property drop zones. Lyra also provides a data pipeline interface for iterative, visual specification of data transformations and layout algorithms. Visualizations created with Lyra are represented as specifications in Vega, a declarative visualization grammar that enables sharing and reuse. We evaluate Lyra's expressivity and accessibility through diverse examples and studies with journalists and visualization designers. We find that Lyra enables users to rapidly develop customized visualizations, covering a design space comparable to existing programming‐based tools.     

A constraint-based querying system for exploratory pattern discovery

In this article we present ConQueSt, a constraint-based querying system able to support the intrinsically exploratory (i.e., human-guided, interactive and iterative) nature of pattern discovery. Following the inductive database vision, our framework provides users with an expressive constraint-based query language, which allows the discovery process to be effectively driven toward potentially interesting patterns. Such constraints are also exploited to reduce the cost of pattern mining computation. ConQueSt is a comprehensive mining system that can access real-world relational databases from which to extract data. Through the interaction with a friendly graphical user interface (GUI), the user can define complex mining queries by means of few clicks. After a pre-processing step, mining queries are answered by an efficient and robust pattern mining engine which entails the state-of-the-art of data and search space reduction techniques. Resulting patterns are then presented to the user in a pattern browsing window, and possibly stored back in the underlying database as relations.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

Algorithms for multidimensional partitioning of static files

The problem of multidimensional file partitioning (MDFP) arises in large databases that are subject to frequent range queries on one or more attributes. In an MDFP scheme, the search attribute space is partitioned into cells, which are mapped to physical disk locations. This mapping preserves the order of the search attribute values so that range queries can be answered most efficiently, while maintaining good performance for other types of queries. Recently, MDFP schemes have been suggested to include both dynamic and static file organizations. Optimal and heuristic MDFP algorithms are developed for the static case. The results of extensive computational experiments show that the proposed heuristics perform better than known static ones. It is also shown that incorporating a static algorithm into a dynamic MDFP such as a grid file at conversion and/or periodical reorganization points significantly improves the resulting storage utilization of the data file and decreases the size of the directory file     

FromDaDy: Spreading Aircraft Trajectories Across Views to Support Iterative Queries

When displaying thousands of aircraft trajectories on a screen, the visualization is spoiled by a tangle of trails. The visual analysis is therefore difficult, especially if a specific class of trajectories in an erroneous dataset has to be studied. We designed FromDaDy, a trajectory visualization tool that tackles the difficulties of exploring the visualization of multiple trails. This multidimensional data exploration is based on scatterplots, brushing, pick and drop, juxtaposed views and rapid visual design. Users can organize the workspace composed of multiple juxtaposed views. They can define the visual configuration of the views by connecting data dimensions from the dataset to Bertin's visual variables. They can then brush trajectories, and with a pick and drop operation they can spread the brushed information across views. They can then repeat these interactions, until they extract a set of relevant data, thus formulating complex queries. Through two real-world scenarios, we show how FromDaDy supports iterative queries and the extraction of trajectories in a dataset that contains up to 5 million data.     

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image—Projection Explorer for Images—a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.     

Cost effective storage space for data cubes

View materialization is one of the most important techniques applied in multidimensional databases. The problem of selecting a set of views for materialization that minimizes queries response time under storage space constraint received significant attention over last twenty years. Many researchers concentrate on designing better view selection methods with respect to the running time or the cost of the solution. This paper summarizes our research on the problem of how much space should be allocated for views materialization to ensure good queries performance. In order to comprehensively investigate the problem and minimize the influence of untypical cases, the experiments described in this paper were done on the large data set, including large data cubes, rarely considered in previous papers. In particular, the relation between the number of data cube views and the space limit expressed as a percentage of the fully materialized data cube size and a multiple of the base view size is analysed. According to our experimental results, the allocation of large space for views materialization is not cost effective.