Architectural support for database visualization

The rapid proliferation and growth of database management systems has resulted in the retention of massive amounts of information for data processing and analysis needs. Many data processing requirements can be satisfied through the use of traditional database languages, such as SQL. These languages retrieve and present query results in record-oriented tables. The table of records format is best for presenting every record, but it cannot give a feel for the overall character of the data set.

[1]  Isabel F. Cruz,et al.  DOODLE: a visual language for object-oriented databases , 1992, SIGMOD '92.

[2]  Phyllis Reisner,et al.  Human Factors Studies of Database Query Languages: A Survey and Assessment , 1981, CSUR.

[3]  Hans-Peter Kriegel,et al.  VisDB: database exploration using multidimensional visualization , 1994, IEEE Computer Graphics and Applications.

[4]  Steven K. Feiner.  Virtual worlds for visualizing information , 1992, Proceedings Supercomputing '92.

[5]  M. Karnaugh.  The map method for synthesis of combinational logic circuits , 1953, Transactions of the American Institute of Electrical Engineers, Part I: Communication and Electronics.

[6]  Tiziana Catarci,et al.  What Happened When Database Researchers Met Usability , 2000, Inf. Syst..

[7]  Hans-Peter Kriegel,et al.  Supporting data mining of large databases by visual feedback queries , 1994, Proceedings of 1994 IEEE 10th International Conference on Data Engineering.

[8]  Tony DeRose,et al.  Toolglass and magic lenses: the see-through interface , 1993, SIGGRAPH.

[9]  James Allan,et al.  Interactive Cluster Visualization for Information Retrieval , 1997 .

[10]  Miles MacLeod,et al.  Usability measurement in context , 1994, Behav. Inf. Technol..

[11]  Wendy T. Lucas,et al.  Delaunay: a database visualization system , 1997, SIGMOD '97.

[12]  Michael Stonebraker,et al.  Supporting fine-grained data lineage in a database visualization environment , 1997, Proceedings 13th International Conference on Data Engineering.

[13]  Richard W. Scamell,et al.  A Human Factors Experimental Comparison of SQL and QBE , 1993, IEEE Trans. Software Eng..

[14]  Tiziana Catarci,et al.  QBD*: A Graphical Query Language with Recursion , 1989, IEEE Trans. Software Eng..

[15]  Ben Shneiderman,et al.  Visual information seeking: tight coupling of dynamic query filters with starfield displays , 1994, CHI '94.

[16]  Heike Hofmann,et al.  Visualizing association rules with interactive mosaic plots , 2000, KDD '00.

[17]  Hans Hagen,et al.  Scientific Visualization: Overviews, Methodologies, and Techniques , 1997 .

[18]  Hans-Peter Kriegel,et al.  Recursive pattern: a technique for visualizing very large amounts of data , 1995, Proceedings Visualization '95.

[19]  Daniel A. Keim,et al.  Pixel-oriented database visualizations , 1996, SGMD.

[20]  Isabel F. Cruz,et al.  User-Defined Visual Languages for Querying Data , 1993 .

[21]  Tiziana Catarci,et al.  Diagrammatic vs. Textual Query Languages: A Comparative Experiment , 1997, VDB.

[22]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[23]  Alfred Inselberg,et al.  Parallel coordinates: a tool for visualizing multi-dimensional geometry , 1990, Proceedings of the First IEEE Conference on Visualization: Visualization `90.

[24]  R. Daniel Bergeron,et al.  Interactive data exploration with a supercomputer , 1991, Proceeding Visualization '91.

[25]  Miron Livny,et al.  DEVise and the JavaScreen: visualization on the web , 2000, Electronic Imaging.

[26]  Isabel F. Cruz.  Expressing Constraints for Data Display Specification: A Visual Approach , 1993 .

[27]  Hans-Peter Kriegel,et al.  Possibilities and Limits in Visualizing Large Databases , 1995, Visual Database Systems.

[28]  Roberto J. Bayardo,et al.  Efficiently mining long patterns from databases , 1998, SIGMOD '98.

[29]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[30]  Peter J. H. King,et al.  Gql, a declarative graphical query language based on the functional data model , 1994, AVI '94.

[31]  Mehmet M. Dalkilic,et al.  Information dependencies , 2000, PODS '00.

[32]  David W. Stemple,et al.  Human factors comparison of a procedural and a nonprocedural query language , 1981, TODS.

[33]  Christopher Ahlberg,et al.  Spotfire: an information exploration environment , 1996, SGMD.

[34]  John Peter Lee,et al.  Data Exploration Interactions and the ExBase System , 1993, Workshop on Database Issues for Data Visualization.

[35]  Donald D. Chamberlin,et al.  Human factors evaluation of two data base query languages: square and sequel , 1975, AFIPS '75.

[36]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[37]  Andreas Buja,et al.  Grand tour methods: an outline , 1986 .

[38]  Georges G. Grinstein,et al.  Iconographic Displays For Visualizing Multidimensional Data , 1988, Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics.

[39]  Moshé M. Zloof.  Query-by-Example: A Data Base Language , 1977, IBM Syst. J..

[40]  David J. DeWitt,et al.  The Wisconsin Benchmark: Past, Present, and Future , 1991, The Benchmark Handbook.

[41]  Jock D. Mackinlay,et al.  The structure of the information visualization design space , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[42]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[43]  Ben Shneiderman,et al.  Dynamic queries for visual information seeking , 1994, IEEE Software.

[44]  Shamkant B. Navathe,et al.  An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.

[45]  Tomasz Imielinski,et al.  Explicit control of logic programs through rule algebra , 1988, PODS '88.

[46]  Ed H. Chi,et al.  A taxonomy of visualization techniques using the data state reference model , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[47]  Christopher Ahlberg,et al.  IVEE: an environment for automatic creation of dynamic queries applications , 1995, CHI '95.

[48]  Daniel A. Keim,et al.  databases and visualization , 1996, SIGMOD '96.

[49]  A. Inselberg,et al.  Parallel coordinates for visualizing multi-dimensional geometry , 1987 .

[50]  Peter P. Chen.  The entity-relationship model: toward a unified view of data , 1975, VLDB '75.

[51]  Rajeev Motwani,et al.  Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.

[52]  E. F. Codd,et al.  A Relational Model for Large Shared Data Banks , 1970 .

[53]  Sunita Sarawagi,et al.  Integrating Mining with Relational Database Systems: Alternatives and Implications. , 1998, SIGMOD 1998.

[54]  Yasuhiko Morimoto,et al.  Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization , 1996, SIGMOD '96.

[55]  Christopher Williamson,et al.  Dynamic queries for information exploration: an implementation and evaluation , 1992, CHI.

[56]  Michael Stonebraker,et al.  Tioga: A database-oriented visualization tool , 1993, Proceedings Visualization '93.

[57]  Daniel A. Keim,et al.  Visual support for query specification and data mining , 1995 .

[58]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[59]  Hans-Peter Kriegel,et al.  VisDB: a system for visualizing large databases , 1995, SIGMOD '95.

[60]  Georges G. Grinstein,et al.  Exvis: an exploratory visualization environment , 1989 .

[61]  Jan Van den Bussche,et al.  An overview of GOOD , 1992, SGMD.

[62]  Matthew Chalmers,et al.  Bead: explorations in information visualization , 1992, SIGIR '92.

[63]  Tiziana Catarci,et al.  Visual Query Systems for Databases: A Survey , 1997, J. Vis. Lang. Comput..

[64]  Heikki Mannila,et al.  Approximate Dependency Inference from Relations , 1992, ICDT.

[65]  Hans-Peter Kriegel,et al.  Visualization Techniques for Mining Large Databases: A Comparison , 1996, IEEE Trans. Knowl. Data Eng..

[66]  Ronald J. Brachman,et al.  The Process of Knowledge Discovery in Databases , 1996, Advances in Knowledge Discovery and Data Mining.