Abstract:
Multi-query data visualization processes, data visualization apparatus, computer-readable media and computer data signals embodied in a transmission medium are provided. According to one aspect of the present invention, a multi-query data visualization process includes inputting a plurality of query objects into a data processing device and identifying features within each of the plurality of query objects that allow comparison to a body of data stored in a database. The process further includes determining relative relationships between each of the plurality of query objects and the body of data and displaying points along a plurality of rays, wherein a position of each of the displayed points corresponds to the determined relative relationship between each respective one of the plurality of query objects and the body of data.

Description:
[0001]    This application is related to U.S. Pat. No. 6,070,133, entitled “Information Retrieval System Utilizing Wavelet Transform”, issued to M. E. Brewster and N. E. Miller on May 30, 2000 and filed on Jul. 21, 1997, which patent is hereby incorporated herein by reference for its teachings. 
     
    
     
       TECHNICAL FIELD  
         [0002]    The present invention relates to multi-query data visualization processes, data visualization apparatus, computer-readable media and computer data signals embodied in a transmission medium.  
         BACKGROUND OF THE INVENTION  
         [0003]    Some conventional information visualization and retrieval systems provide visualizations related to documents or their attributes by representing documents or a group of documents with graphical symbols. Search techniques for identifying a group of documents or portions of documents relative to some set of search criteria have been developed. Most of these techniques also provide some indicia of relevance for each element harvested by the search.  
           [0004]    Examples of search techniques and relevancy evaluation tools are discussed, for example, in “Evaluation of a Tool for Visualization of Information Retrieval Results” by A. Veerasamy and N. Belkin, ACM catalogue no. 0-89791-792-8/96/08. This paper discusses a variety of information retrieval strategies and relationships between the search technique and the relevance or interpretation of search results. In general, searches tend to include an initial phase, during which search strategy is “fine-tuned”, and a second phase, in which specific items are harvested using the fine-tuned search strategy.  
           [0005]    In the first phase, interpretation of search results is critical to successful and efficient modification of search strategy in order to try to optimize retrieval of data of particular relevance to a topic of interest. As the amount of data being searched increases, it is increasingly difficult and time-consuming to examine individual documents or portions of documents in order to assess relative relevance to an inquiry. It may also be increasingly difficult to understand relationships between the query, the search tool being employed and the information produced by the search tool. As a result, search results have been organized in a variety of different ways to try to make selected indicia available to the searcher in order to facilitate comprehension of the search results.  
           [0006]    For example, various types of frequency data may be coupled to specific query elements or search results. As is discussed in the abovenoted article, many search engines will display a list of surrogates (e.g., title, source, author) of the top n-many retrieved items, together with some ranking for each. Such systems do not necessarily provide a clear understanding of why the particular list of items was retrieved, how elements within the list were ranked or how to improve query formulation to arrive at a possibly better set of retrieved data.  
           [0007]    As the information-handling capacity of data manipulation systems increases, more and more data, running from abstracts to full-text displays, can be provided to the user as the user attempts to focus the search results on the topic of interest. However, this can result in increased search time at the first phase of a search, without necessarily improving the search results or understanding of the relationship between the search criteria and the search results.  
           [0008]    The types of search tools generally in use allow a relatively complex query to be formulated and are able to provide indicia regarding relevance of search results to components of the query. However, these tools do not lend themselves to simultaneous multiple complex queries and collective interpretation of results from such queries.  
           [0009]    Accordingly, there is need for visualization systems which provide clear and concise representations of search results that facilitate intuitive understanding of relationships between the search results, the search tool being employed and the queries giving rise to the search results.  
         SUMMARY OF THE INVENTION  
         [0010]    According to one aspect of the present invention, a multi-query data visualization process includes inputting a plurality of query objects into a data processing device and identifying features within each of the plurality of query objects that allow comparison to a body of data stored in a database. The process also includes determining relative relationships between each of the plurality of query objects and the body of data and displaying points along a plurality of rays. Positions of the displayed points correspond to the relative relationships.  
           [0011]    A second aspect of the present invention provides data visualization apparatus including an image device configured to provide a visual image and digital processing circuitry coupled with the image device. The processing circuitry is configured to input a plurality of query objects and to identify features within each of the plurality of query objects that allow comparison to a body of data stored in a database. The processing circuitry is further configured to determine relative relationships between each of the plurality of query objects and the body of data and to control the image device to depict points corresponding to data from the database along each of a plurality of rays. Positions of the displayed points correspond to the relative relationships.  
           [0012]    Another aspect of the invention provides computer usable code. The computer usable code is configured to cause digital processing circuitry to identify features of each of a plurality of query objects that allow comparison to a body of data stored in a database and to determine relative relationships between each of the plurality of query objects and the body of data. The computer usable code is also configured to control an image device to depict points corresponding to data from the database along each of a plurality of rays. Positions of the displayed points correspond to the relative relationships.  
           [0013]    A further aspect of the present invention includes a computer data signal embodied in a transmission medium. The signal includes computer usable code configured to input a plurality of query objects into a data processing device and to determine relative relationships between each of the plurality of query objects and a body of data stored in a database. The signal also includes computer usable code configured to control an image device to depict points corresponding to data from the database along each of a plurality of rays. Positions of the displayed points correspond to the relative relationships.  
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0014]    Preferred embodiments of the invention are described below with reference to the following accompanying drawings.  
         [0015]    [0015]FIG. 1 is a perspective view of an exemplary data visualization apparatus comprising a digital computer, in accordance with an embodiment of the present invention.  
         [0016]    [0016]FIG. 2 is a functional block diagram of exemplary components of the data visualization apparatus of FIG. 1, in accordance with an embodiment of the present invention.  
         [0017]    [0017]FIG. 3 shows an exemplary visual representation corresponding to II exemplary data shown upon an imaging medium of an appropriate image device, in accordance with an embodiment of the present invention.  
         [0018]    [0018]FIG. 4 is a graphical representation of an exemplary search results display depicted using the digital computer following reorganization of the data in response to user input, in accordance with an embodiment of the present invention.  
         [0019]    [0019]FIG. 5 shows another exemplary visual representation of the exemplary search results shown in the visual representation of FIGS. 3 and 4, in accordance with an embodiment of the present invention.  
         [0020]    [0020]FIG. 6 shows an exemplary visual representation corresponding to another form of multi-query based on different forms of similarity to a given graphical object, representing a query or hypothesis, in accordance with an embodiment of the present invention.  
         [0021]    [0021]FIG. 7 is a flow chart illustrating an exemplary process to depict data, in accordance with an embodiment of the present invention. 
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0022]    This disclosure of the invention is submitted in furtherance of the constitutional purposes of the U.S. Patent Laws “to promote the progress of science and useful arts” (Article 1, Section 8).  
         [0023]    Referring to FIG. 1, a data visualization apparatus  10  is illustrated, in accordance with an embodiment of the present invention. The depicted data visualization apparatus  10  is implemented as a digital computer such as an Ultra 10 elite 3D workstation available from Sun Microsystems Inc. in one exemplary embodiment. Software utilized by the apparatus  10  includes mathematical, analytical and graphical software such as Rogue Wave Software Object-Oriented Libraries including Tools.h++ (Version 7), Math.h++ (Version 6), LAPACK.h++ (Version 2), and Analytics.h++ (Version 1) and software graphics package OpenGL™ available from Silicon Graphics, Inc. Other alternatives are possible. The depicted data visualization apparatus  10  is configured to operate under a multi-user, multi-tasking operating system, such as UNIX™. Other configurations of data visualization apparatus  10  are provided in other embodiments.  
         [0024]    As shown, data visualization apparatus  10  includes a plurality of image devices  12 , a housing  14  and a user interface  16 . Image devices  12  are individually configured to visually depict data such as visual representation  18  described in detail below. Exemplary image devices  12  comprise a monitor  15  and a printer  17 . Image devices  12  comprise other devices configured to depict data in other embodiments. Exemplary devices of user interface  16  include a keyboard  13  and a mouse  19  as shown.  
         [0025]    [0025]FIG. 2 is a functional block diagram of exemplary components of the data visualization apparatus  10  of FIG. 1, in accordance with an embodiment of the present invention. In particular, housing  14  is configured to house a processor  20 , a plurality of storage devices  22  and a network interface  24 . In the illustrated configuration, storage devices  22  include memory  26  and disk storage device  28 . Storage devices  22  comprise computer usable media configured to store computer usable code and data. Exemplary memory  26  includes random access memory (RAM) and read only memory (ROM). Exemplary disk storage devices  28  include floppy disks and hard disks. Other storage devices such as a CD-ROM device are utilized in other configurations.  
         [0026]    An exemplary network interface  24  comprises a network interface card configured to couple with an external network such as a public switched telephone network, a packet switched network, such as the Internet etc.  
         [0027]    Data visualization apparatus  10  is configured to access data and visually depict such data organized as the visual representation  18  (FIGS. 1 and 3) with respect to a plurality of query objects and/or events using the image devices  12  in the described embodiment. In the depicted configuration, the visual representation  18  portrays multiple documents or information organized along vectors or rays extending outwardly from a common origin or locus. As used herein, the term “ray” is defined to mean a geometric construct having an origin and a direction, and may correspond to a linear or non-linear construct, such as a spiral, or which may be a directed region of space or volume, such as a half-plane or a curved planar surface. The rays represent the possible variance in relative relationship between the plurality of query objects and the body of data. Documents are illustrated as points spaced apart from the common origin or locus by varying distances. The common origin or locus is representative of the limit of the relative relationships.  
         [0028]    The processor  20  comprises digital processing circuitry and is coupled with the image devices  12 . The processor  20  is configured to access data from the storage devices  22 , the network interface  24  and the user interface  16 . The processor  20  is configured to generate the visual representation  18  corresponding to documents, references and/or events within the accessed data as described in detail below. The processor  20  further controls the image devices  12  to depict the visual representation  18  corresponding to the accessed data.  
         [0029]    [0029]FIG. 3 shows an exemplary visual representation  18  corresponding to exemplary data shown upon an imaging medium  30  of an appropriate image device  12 , in accordance with an embodiment of the present invention. The imaging medium  30  is suitable to visually depict the visual representation  18  and in exemplary configurations comprises paper for a printer image device  17  (FIG. 1), a display screen of a monitor image device  15  etc. Other types of imaging media  30  may be used in other embodiments.  
         [0030]    [0030]FIG. 3 also shows six query objects or inquiries  31 - 36  grouped about a central point or locus  37 . Multiple documents or information each represented by points  38  are organized along rays  41 - 46  arranged about the central point  37 . The rays  41 - 46  extend outwardly from the common origin or locus  37  where a distance separating each document  38  from the common origin or locus  37  representing the query objects  31 - 36  represents a degree of similarity or lack thereof with respect to the hypotheses or query objects  31 - 36 . While the rays  41 - 46  are represented as six rays equiangularly spaced about the locus  37 , it will be appreciated that more or fewer query objects  31 - 36  could be employed, and that the rays  41 - 46  need not be equiangularly spaced about the locus  37 .  
         [0031]    The depicted data elements  38  may corresponds to the occurrence of particular items (e.g., country names, agricultural products, political movements, legal precedents, technical topics or keywords, image characteristics etc.) within a body of data, for example. Any type of data may be depicted within the visual representation  18 . Types of data that may be analyzed include, for example, images corresponding to tissue samples, micrographs of metal samples, fingerprints or other biometric indicia, or word processing or text-containing files corresponding to legal cases, patent and/or technical publication databases, web documents, audio files of human speech or any other type of data that may be organized into a database.  
         [0032]    As used herein, the term “query” is defined to mean an information object to be compared to objects in a database. A query could be one or more words, an image, results of a simulation, a color, a web page, a document, a sound file containing an audio conversation etc. The user is interested in the relative relation between the query and the data in the database. The relationship of interest may include similarity, containment, antithesis, shared attribute etc. The query may be the same kind of entity as the data in the database (for example, using a document as a query to be compared to WWW documents), or it may be different (for example, if the query is a color, and the goal is to find images containing that color). In another example, the query is a scenario and the objects  38  are extracted facts that match elements of the scenario.  
         [0033]    The queries may be generated by a single individual or may be generated by multiple people working in a team-oriented or collaborative environment. Thus, for example, FIG. 3 might represent a method for exploring how six different people&#39;s viewpoints relate to the information in the database.  
         [0034]    Examples of systems intended to assign numerical surrogates facilitating vector representation for attributes of data within a database in order to promote analysis of bodies of data and data extraction or document retrieval from of bodies of data are described in U.S. Pat. No. 5,553,226, entitled “System For Displaying Concept Networks” and issued to Kiuchi et al.; U.S. Pat. No. 5,950,196, entitled “System And Methods For Retrieving Tabular Data From Textual Sources” and issued to Pyreddy et al.; U.S. Pat. No. 5,659,732, entitled “Document Retrieval Over Networks Wherein Ranking And Relative Scores Are Computed At The Client For Multiple Database Documents” and issued to Kirsch; U.S. Pat. No. 5,826,261, entitled “System And Method For Querying Multiple, Distributed Databases By Selective Sharing Of Local Relative Significance Information For Terms Related To The Query” and issued to Spencer, which patents are hereby incorporated herein by reference for their teachings.  
         [0035]    An exemplary system for carrying out similar sorting and identification with respect to multimedia data is described in U.S. Pat. No. 5,873,080, entitled “Using Multiple Search Engines To Search Multimedia Data” and issued to Coden et al., which patent is hereby incorporated herein by reference for its teachings. An example of a system for examining groups of documents and for providing two-dimensional displays related thereto is described in U.S. Pat. No. 5,625,767, entitled “Method And System For Two-Dimensional Visualization Of An Information Taxonomy And Of Text Documents Based On Topical Content Of The Documents” and issued to Bartell et al., which patent is hereby incorporated herein by reference for its teachings. Other tools that may be usefully employed include vector space models and statistical natural language processing techniques.  
         [0036]    Another example of a system for facilitating human interaction with large bodies of information is the Spatial Paradigm for Information Retrieval and Exploration program developed at the Pacific Northwest Laboratory in Richland Wash. and described, for example, in “Visualizing The Non-Visual: Spatial Analysis And Interaction With Information From Text Documents”, published in Proceedings of IEEE &#39;95 Information Visualization, pages 51-58, Atlanta Ga., October 1995, available through the IEEE Service Center, and hereby incorporated herein by reference for teachings on information processing and display. The SPIRE™ browsing system supports two-dimensional displays of data (e.g., the Galaxy display, similar to FIG. 5, infra) that have been processed to provide feature vector data according to thematic content.  
         [0037]    The depicted visual representation  18  graphically presents the relationship of each data object  38  in a database to each of the query objects  31 - 36 . The relationship of each data object  38  to a specific query object is indicated by the placement of a point representing the data object  38  along a single ray such as  41  corresponding to the query object  31 . The proximity of a point along the ray to the locus  37  indicates the strength of the relationship between the query object and the data object represented by the point. In the current embodiment, the closer the point  38  is to the locus  37 , the more similar the data object  38  is to the ray&#39;s query object. In one embodiment, two-dimensional representations of n-dimensional vectors are prepared using Sammon mapping, as is known in the art. Sammon mapping and other cluster-mapping techniques for representation of n-dimensional vectors in a two-dimensional space are discussed, for example, in U.S. Pat. No. 5,897,627, entitled “Method Of Determining Statistically Meaningful Rules” and issued to Leivian et al. and U.S. Pat. No. 5,891,729, entitled “Method For Substrate Classification” and issued to Behan et al., which patents are hereby incorporated herein by reference for their teachings.  
         [0038]    Additional techniques for mapping data are discussed in U.S. Pat. No. 6,031,537, entitled “Method And Apparatus For Displaying A Thought Network From A Thought&#39;s Perspective” and issued to Hugh; U.S. Pat. No. 6,076,088, entitled “Information Extraction System And Method Using Concept Relation Concept (CRC) Triples” and issued to Paik et al.; U.S. Pat. No. 6,026,388, entitled “User Interface And Other Enhancements For Natural Language Information Retrieval System And Method” and issued to Liddy et al.; and U.S. Pat. No. 5,576,954, entitled “Process For Determination Of Text Relevancy” and issued to Driscoll, which patents are hereby incorporated herein by reference for their teachings.  
         [0039]    Query objects  31 - 36  in accordance with the present invention can take many forms. Query objects  31 - 36  may correspond to situations where the user does not know much about the expected results, but does know what form a relevant response might take. In this case, the interaction of the user with the database is similar to a conventional search, such as a Boolean keyword search.  
         [0040]    Query objects  31 - 36  may represent efforts to browse an information space. In this instance, the user is looking for something, but does not know what the result might look like. Query objects  31 - 36  may also represent attempts to “reality test” an idea or concept. In this case, the user has a mental model of the content some part of the database, but would like to determine whether the data supports or refutes that the mental model has validity.  
         [0041]    Examples of types of query objects or hypotheses  31 - 36  that the user might be interested in may include trying to locate legal precedents for a given fact pattern, trying to locate patents or technical publications relating to a type of device, process or model, searching for information in political speeches, government reports and the like, searching for information regarding chronological developments on a given topic, searching for a subset of images including a some specific type of image or data, searching a series of broadcasts for specific speech patterns, jingles or content or any other form of organized search of a body of data.  
         [0042]    The processor  20  controls the image device  12  to arrange the visual representation  18  relative to a central locus  37 . The locus  37  may be provided at other locations relative to the visual representation  18  in other arrangements. Further, the locus  37  may be depicted or not shown at all in particular configurations of the visual representation  18 .  
         [0043]    [0043]FIG. 4 is a graphical representation of exemplary search results in visual representation  18  depicted using the digital computer following specification of a relevance threshold  52  in response to user input, in accordance with an embodiment of the present invention. The processor  20  (FIG. 2) is configured to display the rays  41 - 46  corresponding to user-input query objects  31 - 36  and to determine relative relationships between the points  38  distributed along the rays  41 - 46  and data stored in the database and to then represent a subset of the data having relevance to the query objects as points  38  distributed along the vectors  41 - 46  within the relevance threshold  52 . In one embodiment, the relevance threshold  52  is represented by a circle or other geometric shape formed about the common origin  37 .  
         [0044]    In one embodiment, the user is able to gauge a probable relevance of data represented by a given point, e.g., point  54 , found along one of the rays  41 - 46 , e.g.,  43 , by noting a distance separating the given object, e.g., that represented by the point  54 , from the common origin  37 . The s object corresponding to the point  54  actually has similar relevance to each of the query objects  31 - 36  as shown by the arcs  55  coupling the representation of the object  54  on the ray  43  to representations of the object  54  on others of the rays  41 ,  42  and  44 - 46 . In the example of FIG. 4, the user has requested that the system show all points falling within the relevance threshold  52  for all queries. In this instance, only two objects, represented by the points  54  and  56 , meet this criteria. Representations of the object  56  on each of the rays  41 - 46  are interconnected by arcs  57 .  
         [0045]    In one embodiment, the user may select one of the objects corresponding to the points  54  and  56 , e.g., point  54 . The selection can be made, for example, using a tactile feedback input device such as a mouse or keyboard (e.g., using arrow keys or the tab key, followed by the enter key). In response to user selection of the given point  54 , a display of data relating to the object corresponding to the given point  54  is provided. The display may include information such as author, frequency tables for occurrence of selected terms in the query, probable status for the object corresponding to the point  54  vis-a-vis the query  33  occurring within the object, confidence factor and the like.  
         [0046]    For example, in one embodiment, the user may be provided with a text display corresponding to a document represented by the given point  54 . In one embodiment, a separate image device displays text corresponding to the document represented by the given point  54 . In one embodiment, the user may be provided with a text file corresponding to a portion of a document where the portion has been determined to be that portion of the document that includes reference to a specific theme or idea.  
         [0047]    In one embodiment, the user may request all objects within the specified distance of all but one of the query objects  31 - 36 , or all but two etc., and to then obtain a display of the ensemble of objects after re-calculation of relative relationships between the query objects  31 - 36  and the collection of objects in the database. In one embodiment, the user may select (e.g., click on) one or more of the queries to turn that query off and to then obtain a display of the ensemble of points after re-calculation of relative relationships between the query objects  31 - 36  and the collection of objects in the database.  
         [0048]    [0048]FIG. 5 shows another exemplary visual representation  58  of the exemplary search results shown in the visual representation  18  of FIGS. 3 and 4, in accordance with an embodiment of the present invention. In FIG. 5, relative distance represents similarity or lack thereof between distinct points of the representation  58 . For example, one method of placing the points (e.g.,  38 ,  31 - 36 ,  54 ) is to use Sammon projection or other multidimensional scaling methods, as described in “Multivariate Analysis” by K. V. Mardia, J. T. Kent and J. M. Bibby, Academic Press Ltd., London, U.K., 1979 (ISBN 0-12-471252-5), which is hereby incorporated herein by reference for its teachings. In one embodiment, the similarity between the query objects and the data in the database is weighted more strongly in determining the positions of points  38  than the similarity among data in the database. In one embodiment, the user may control the weighting scheme, to modify the amount of weighting or to limit it to only some of the query objects  31 - 36  or some of the database objects. The representations  18  and  58  are linked so that elements (e.g.,  31 - 36 ,  54 ,  56 ) selected in one of the representations  18 ,  58  also are selected in the other of these representations  18  and  58 .  
         [0049]    [0049]FIG. 6 shows an exemplary visual representation  60  corresponding to another form of multi-query based on different forms of similarity to a given graphical object  62 , representing a query or hypothesis, in accordance with an embodiment of the present invention. FIG. 6 shows examples of a nearest match  64  interconnected by dashed lines  65  and appearing in each of four different regions  66 - 72 , where each region  66 - 72  corresponds to an attribute such as black/white mix content, curve content, horizontal component content or spatial frequency content. The object  62  could represent a tissue sample, a metallurgical micrograph, biometric image data or any other type of image data.  
         [0050]    [0050]FIG. 7 is a flow chart illustrating an exemplary process P 1  to depict data, in accordance with an embodiment of the present invention.  
         [0051]    Initially, the processor  20  (FIG. 2) executes a set-up procedure. For example, the processor  20  creates a window having a menu bar and/or a drawing area within the imaging medium of an appropriate image device  12 .  
         [0052]    The process P 1  then proceeds to a step S 1 . In the step S 1 , the user enters a set of query objects  31 - 36 .  
         [0053]    In a step S 2 , the query objects  31 - 36  are converted to n-dimensional feature data. Conversion to vector data may be carried out using any appropriate algorithm, with the type of algorithm needed being determined in part by the nature of the data forming the query objects  31 - 36 .  
         [0054]    Next, the processor  20  proceeds to a step S 3  to access data objects to be visually depicted by the image device  12 . Such data objects typically include references, events or images. In one embodiment, the data consist of entire images or documents. In one embodiment, the data are processed to determine boundaries of portions of data elements, such as documents that are relevant to one or more topics, and the data are broken down into subsets, some of which will be more relevant than others to any given query. In the current embodiment, the feature vectors have already been calculated for the data objects in  38  in the database and are merely accessed in this step. In an alternate embodiment, feature vectors for the data objects  38  could be created or modified based on the queries input in the step S 1 .  
         [0055]    In a step S 4 , the n-dimensional feature vectors of the data objects and the query objects are compared to one another. The step S 4  determines relationships between each of the data objects  38  in the database and the query objects  31 - 36 .  
         [0056]    In a step S 5 , the processor  20  projects the relationships calculated in the step S 4  to points along the query rays as seen in FIG. 3. The plurality points along each query ray corresponds to the elements  38 . The plurality of query rays corresponds to the query objects  31 - 36 .  
         [0057]    In a step S 6 , the processor  20  may optionally reduce the n 12  dimensional feature vectors of the data objects and the query objects to two- or three- dimensional vectors or points in an alternate projection. In one embodiment, the data object and the query object feature vectors are converted to two-dimensional points using a Sammon mapping as seen in FIG. 5.  
         [0058]    In a step S 7 , the processor  20  causes the projected points representing the data objects  38  and the query objects  31 - 36  to be displayed on one of the display devices  12 . In one embodiment, displays of the rays depicting relationships between the data objects and the query objects such as that of FIG. 3 are shown. In one embodiment, displays with alternate projections such as that of FIG. 5 are shown.  
         [0059]    In a step S 8 , a relevance threshold is determined. In one embodiment, this results in a display such as that of FIG. 4. In one embodiment, the relevance threshold  52  is set by a user. In one embodiment, the relevance threshold  52  is set according to predetermined characteristics. In one embodiment, the relevance threshold is user-adjustable.  
         [0060]    In a step S 9 , a user examines the displayed data. The user may select one or more of the formats illustrated in FIGS.  3 - 5 , or may flip from one display type to another.  
         [0061]    In a query task S 10 , the process P 1  determines when the user wishes to examine attributes of a given point  38  in a display in more detail. When the user wishes to examine attributes of the given point in more detail, control passes to a step S 11 . When the user does not wish to examine attributes of any points  38  in more detail, or when the user has completed this process, control passes to a query task S 12 .  
         [0062]    When the user wishes to examine attributes of a given point  38  in more detail, the user may select a limited amount of information (e.g., author, keyword frequency, limited text portions or the like) or more comprehensive information (e.g., a full text version of an object or a detailed image of an object) in the step S 11 . Control then passes back to the step S 9 .  
         [0063]    In the query task S 12 , the process P 1  determines when the user wishes to eliminate one or more of the objects  54  or  56 . When the user does not wish to eliminate any elements, the process P 1  passes control to a query task S 13 . When the user does wish to alter or eliminate one or more of the objects such as  54 , control passes back to the step S 6 .  
         [0064]    In the query task S 13 , the process P 1  determines when the user wishes to alter or remove one or more of the query objects  31 - 36 . When the user wishes to alter one or more of the query objects  31 - 36 , the process P 1  passes control to a step S 14 . When the user does not wish to alter or remove one or more of the query objects  31 - 36 , the process P 1  passes control to a query task S 15 .  
         [0065]    In the step S 14 , the user alters or removes one or more of the query objects  31 - 36 . The process P 1  then passes control back to the step S 2 .  
         [0066]    In the query task S 15 , the process P 1  determines when the user wishes to add one or more new queries. When the user does not wish to add any new queries, the process P 1  ends. When the user wishes to add one or more new queries, the process P 1  passes control back to the step S 1 .  
         [0067]    The processor  20  is configured in one embodiment to adjust control of the data visualization apparatus  12  responsive to input from a user via the user interface  16 , via the network interface  24 , or other modes. For example, a user may request new data, new time or reference resolution, a curve type for the components, a change in the order of the components or may select or deselect objects with reference to specific ones of the query objects  31 - 36  or all of them etc. The processor  20  is configured to re-execute appropriate portions of the process P 1  responsive to such changes or requests from a user.  
         [0068]    In compliance with the statute, the invention has been described in language more or less specific as to structural and methodical features. It is to be understood, however, that the invention is not limited to the specific features shown and described, since the means herein disclosed comprise preferred forms of putting the invention into effect. The invention is, therefore, claimed in any of its forms or modifications within the proper scope of the appended claims appropriately interpreted in accordance with the doctrine of equivalents.