Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project

The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system

Diagrammatic-based Query Formulator

Database is a valuable asset of any organization. Working with database has become more and more frequent and necessary. Unfortunately, the current applications only support users with text-based queries which users have to input manually. No ad-hoc queries can be done unless the application user has some knowledge of SQL Queries. Consequently, this web-based application is developed as a tool for users to easily manipulate database. This application will present database as structured diagrams. This will allow users to have a concise and clear view of database. Besides, this application also supports real-time interaction, which will enable users to query the database interactively and visually. As a consequence, less time and effort will spent on querying database to get the required data

Using Visualization to Support Data Mining of Large Existing Databases

In this paper. we present ideas how visualization technology can be used to improve the difficult process of querying very large databases. With our VisDB system, we try to provide visual support not only for the query specification process. but also for evaluating query results and. thereafter, refining the query accordingly. The main idea of our system is to represent as many data items as possible by the pixels of the display device. By arranging and coloring the pixels according to the relevance for the query, the user gets a visual impression of the resulting data set and of its relevance for the query. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. By using multiple windows for different parts of the query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. To support complex queries, we introduce the notion of approximate joins which allow the user to find data items that only approximately fulfill join conditions. We also present ideas how our technique may be extended to support the interoperation of heterogeneous databases. Finally, we discuss the performance problems that are caused by interfacing to existing database systems and present ideas to solve these problems by using data structures supporting a multidimensional search of the database

A general framework for positioning, evaluating and selecting the new generation of development tools.

This paper focuses on the evaluation and positioning of a new generation of development tools containing subtools (report generators, browsers, debuggers, GUI-builders, ...) and programming languages that are designed to work together and have a common graphical user interface and are therefore called environments. Several trends in IT have led to a pluriform range of developments tools that can be classified in numerous categories. Examples are: object-oriented tools, GUI-tools, upper- and lower CASE-tools, client/server tools and 4GL environments. This classification does not sufficiently cover the tools subject in this paper for the simple reason that only one criterion is used to distinguish them. Modern visual development environments often fit in several categories because to a certain extent, several criteria can be applied to evaluate them. In this study, we will offer a broad classification scheme with which tools can be positioned and which can be refined through further research.

The design and implementation of a meaning driven data query language

We present the design and implementation of a Meaning Driven Data Query Language - MDDQL - which aims at the construction of queries through system made suggestions of natural language based query terms for both scientific application domain terms and operator/operation ones. A query construction blackboard is used where query language terms are suggested to the user in its preferred natural language and in a name centered way, together with their connotation. This helps in understanding the meaning of the terms and/or operators or operations to be included in the query. Furthermore, the construction of the query turns out to be an incremental refinement of the query under construction through semantic constraints, where only those domain language terms and/or operators/operations are suggested which result into meaningful combinations of query terms as related to the scientific application domain semantics. Therefore, semantically meaningless queries can be prevented during the query construction. Such a semantics aware mechanism is not available in conventional database query languages such as SQL, where one is allowed to execute a query calculating, for example, the average of numerical data values whereas they represent the codes of categorical values. Moreover, no familiarity with the semantics of complex database schemes or interpretation of the symbols (names of classes/tables/attributes, value codes) underlying the storage model, as well as familiarity with the syntax of a database specific query language are needed by the end-user. The constructed query can be submitted to the MDDQL query interpretation and transformation engine, where the corresponding SQL-query is generated and delegated to a DBMS (e.g., Oracle, MSAccess, SQL-Server). Generation of SQL-statements addressing NF2 data models such as those provided by the object-relational Oracle DBMS is also enabled. The query result is presented in a table based form where all storage model symbols are interpreted and can be exported for the usage with statistical software packages (e.g., SPSS)

Diagrammatic-based Query Formulator

Database is a valuable asset of any organization. Working with database has become more and more frequent and necessary. Unfortunately, the current applications only support users with text-based queries which users have to input manually. No ad-hoc queries can be done unless the application user has some knowledge of SQL Queries. Consequently, this web-based application is developed as a tool for users to easily manipulate database. This application will present database as structured diagrams. This will allow users to have a concise and clear view of database. Besides, this application also supports real-time interaction, which will enable users to query the database interactively and visually. As a consequence, less time and effort will spent on querying database to get the required data

A Tutorial on Visual Representations of Relational Queries

Query formulation is increasingly performed by systems that need to guess a user's intent (e.g. via spoken word interfaces). But how can a user know that the computational agent is returning answers to the "right" query? More generally, given that relational queries can become pretty complicated, how can we help users understand existing relational queries, whether human-generated or automatically generated? Now seems the right moment to revisit a topic that predates the birth of the relational model: developing visual metaphors that help users understand relational queries. This lecture-style tutorial surveys the key visual metaphors developed for visual representations of relational expressions. We will survey the history and state-of-the art of relationally-complete diagrammatic representations of relational queries, discuss the key visual metaphors developed in over a century of investigating diagrammatic languages, and organize the landscape by mapping their used visual alphabets to the syntax and semantics of Relational Algebra (RA) and Relational Calculus (RC).Comment: 4 page tutorial paper at VLDB 2023, tutorial web page with slides to be posted in time: https://northeastern-datalab.github.io/visual-query-representation-tutorial/. arXiv admin note: text overlap with arXiv:2208.0161