Selfridge, P. D., Srivastava, D., Wilson, L. O., IDEA: Interactive Data Exploration and Analysis. SIGMOD '96, Montreal, Canada 1996  Home/Search   Document Details and Download   Summary   Related Articles   Check

....in Conceptual Knowledge Processing aims at developing conceptual knowledge systems by extending the functionalities of conceptual data systems, especially by logic based components. As Formal Concept Analysis and Description Logics are closely related and have similar purposes (see, e.g. 4] [19]) first steps in integrating both theories have been made ( 1] 2] 16] 21] For hybrid knowledge processing, an extension of conceptual data systems is foreseen by incorporating statistical and computational components [23] This indicates a promising development in terms of extending ....

Selfridge, P. D., Srivastava, D., Wilson, L. O., IDEA: Interactive Data Exploration and Analysis. SIGMOD '96, Montreal, Canada 1996

.... allowing dynamic user interaction through direct manipulation paradigms, it is possible to traverse larger information spaces in a shorter time [38] In both academia and industry alike, signi cant e ort has thus been spent on developing e ective methods to display and visually explore information [1, 40, 39, 37, 32, 16, 36, 20, 30]. Most visualization techniques nowadays still execute on data that is rst fetched from the le system into main memory. However, as data is being generated at an ever increasing rate and typical sizes of datasets become larger in the order of giga bytes, current datasets can no longer be held ....

....because the server caches some of the old objects required by the client. 7 Related Work 7. 1 Visual Exploration Systems Much work has been done in recent years on visual interaction tools, including [45, 19, 9, 18, 23, 21, 17] Integrated visualization database systems such as Tioga [40] IDEA [37] and DEVise [32] represent the work most close related to ours in terms of developing tools for visual data exploration support. The speci c approaches taken are however di erent. Tioga [40, 2] implements a multiple browser architecture for a recipe, a visual query. The system is able to cache the ....

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P. G. Selfridge, D. Srivastava, and L. O. Wilson. Idea: Interactive data exploration and analysis. In Proc of the

....needed, instead we put a layer on top of SQL where most of the intelligent data processing is done. Database queries are cached in the DMtools to improve performance and re usability. Other toolbox approaches to data analysis include the IDEA (Interactive Data Exploration and Analysis) system [14], where the authors identify ve general user requirements for data exploration: Querying (the selection of a subset of data according to the values of one or more attributes) segmenting (splitting the data into non overlapping sub sets) summary information (like counts or averages) ....

P.G. Selfridge, D. Srivastava and L.O. Wilson, IDEA: Interactive Data Exploration and Analysis, Proceedings of the ACM SIGMOD International Conference on Management of Data, 1996.

....SQL extension is needed, instead we put a layer on top of SQL where most of the intelligent data processing is done. Database queries are cached to improve performance and re usability. Other toolbox approaches to data analysis include the IDEA (Interactive Data Exploration and Analysis) system [12], where the authors identify five general user requirements for data exploration: Querying (the selection of a subset of data according to the values of one or more attributes) segmenting (splitting the data into non overlapping sub sets) summary information (like counts or averages) ....

P.G. Selfridge, D. Srivastava and L.O. Wilson, IDEA: Interactive Data Exploration and Analysis, Proceedings of the ACM SIGMOD International Conference on Management of Data, 1996.

....4 discusses our scalable parallel algorithms for predictive modelling, and Section 5 gives an outlook to future work. 2 Related work There are several projects describing toolbox like approaches to data exploration. The authors of the IDEA (Interactive Data Exploration and Analysis) system [21] identify five general user requirements for data exploration: Querying (the selection of a subset of data according to the values of one or more attributes) segmenting (splitting the data into non overlapping sub sets) summary information (like counts or averages) integration of external tools ....

P.G. Selfridge, D. Srivastava and L.O. Wilson, IDEA: Interactive Data Exploration and Analysis, Proceedings of the ACM SIGMOD International Conference on Management of Data, 1996.

....and finds patterns of play coaches can Ronald J. Brachman, Tom Khabaza, Willi Kloesgen, Gregory Piatetsky Shapiro, and Evangelos Simoudis TERRY WIDENER 44 November 1996 Vol. 39, No. 11 COMMUNICATIONS OF THE ACM use right away; and AT T s Interactive Data Exploration and Analysis (IDEA) system [11], which focuses on understanding the market s reaction to promotions, new service offerings, and ongoing advertisements. IDEA also has an intuitive visual language for representing data mining procedures and is especially powerful for segmenting data, an operation very important in marketing ....

Selfridge, P.G., Srivastava, D., and Wilson, L.O. IDEA: Interactive Data Exploration and Analysis. In Proceedings of SIGMOD96 (Montral, June 1996). ACM Press, New York, 1996, pp. 24--34.

....get a glimpse at the final result very quickly and use this information to change the ongoing process. The Control system among others includes tools for interactive data aggregation, data visualisation and data mining. The authors of the IDEA (Interactive Data Exploration and Analysis) system [13] describe five general user requirements for data exploration: 1) Querying, i.e. the selection of a subset of data according to the values of one or more attributes, 2) segmenting, i.e. splitting the data into non overlapping sub sets according to the values of one or more attributes, 3) ....

P.G. Selfridge, D. Srivastava and L.O. Wilson, IDEA: Interactive Data Exploration and Analysis, Proceedings of theACM SIGMOD International Conference on Management of Data, 1996.

....this model relies on the history list to update the visualization. Research about interactive exploration has emerged in the context of large, less dynamic data, like databases. Such endeavors are focused on finding relations and data of interest rather than monitoring an evolving activity. IDEA [SSW96] supports interactive database exploration and data analysis. It introduces a graphical history mechanism and re usable representation of analysis and exploration sessions. Exploration is viewed as the process of identifying the data to be analyzed. VQE [DKR97] is a visual query language that uses ....

Peter G. Selfridge, Divesh Srivastava, and Lynn O. Wilson. IDEA: Interactive data exploration and analysis. SIGMOD Record (ACM Special Interest Group on Management of Data), 25(2):24--34, June 1996.

....is that subsumption relations among queries can be inferred, allowing them to be automatically organized into the knowledge base. On the other hand, in later work the same group reverted to a simpler knowledge representation system to decrease the overhead and allow exploration of larger data sets [12]. IMACS visualizations do not support direct manipulation interaction, and it uses a textual query language. Queries are somewhat more expressive than VQE s. 6. SUMMARY VQE combines a GQL style intentional visual query language with direct manipulation data exploration capabilities as found in ....

P. G. Selfridge, D. Srivastava, and L. O. Wilson. Idea: Interactive data exploration and analysis. In Proceedings of SIGMOD 1996, 1996.

....brushes are actually computed rather than large ones. Thus, the amount of the data being read from the database, and implicitly the overall processing, is significantly reduced. 6 Related Work Visualization database integration. Integrated visualization database systems such as Tioga [15] IDEA [14], DEVise [12] represent the work closest related to ours in terms of problem area. The approaches are however different. Tioga [15] implements a multiple browser architecture for what they call a recipe, a visual query. However, the problem of query translation is not present since database ....

....terms of problem area. The approaches are however different. Tioga [15] implements a multiple browser architecture for what they call a recipe, a visual query. However, the problem of query translation is not present since database queries are explicitly specified by the graphical interface. IDEA [14] is an integrated set of tools to support interactive data analysis and exploration. Some constraints on the data model are imposed by the application domain, but on line query translation and memory management are not addressed. In DEVise [12] a set of query and visualization primitives to ....

P. G. Selfridge, D. Srivastava, and L. O. Wilson. Idea: Interactive data exploration and analysis. In ACM SIGMOD Intl Conf on Management of Data, pages 24--34, 1996.

....concatenation of all ancestor codes could exceed the available precision for deep trees. A fragmentation of the initial tree and consequently additional joins would thus need to be performed. Visualization database integration. Integrated visualization database systems such as Tioga [27] IDEA [25], DEVise [20] represent probably the work closest related to ours in terms of problem 23 area. The approaches are however different. Tioga [27] implements a multiple browser architecture for what they call a recipe, a visual query. The system is able to buffer the computed data; however, the ....

....different. Tioga [27] implements a multiple browser architecture for what they call a recipe, a visual query. The system is able to buffer the computed data; however, the problem of query translation is not present since database queries are explicitly specified by the graphical interface. IDEA [25] is an integrated set of tools to support interactive data analysis and exploration. Some constraints on the data model are imposed by the application domain, but on line query translation and memory management are not addressed. In DEVise [20] a set of query and visualization primitives to ....

P. G. Selfridge, D. Srivastava, and L. O. Wilson. Idea: Interactive data exploration and analysis. In Proc of the 1996 ACM SIGMOD Intl Conf on Management of Data, Montreal, Quebec, Canada, June 4-6, 1996, pages 24--34. ACM Press, 1996.

....is that subsumption relations among queries can be inferred, allowing them to be automatically organized into the knowledge base. On the other hand, in later work the same group reverted to a simpler knowledge representation system to decrease the overhead and allow exploration of larger data sets [17]. IMACS visualizations do not support direct manipulation interaction, and it uses a textual query language. Queries are somewhat more expressive than VQE s. 6 FUTURE WORK 6.1 Expressiveness VQE lacks quantification, disjunction, and negation. This is not a fatal shortcoming, because ....

....solution seems to be a preprocessing step to download data that is expected to be most relevant, before the direct manipulation system takes over. Doan [7] has created an interface for previewing the data before downloading. We will incorporate some of these ideas as the need arises. Selfridge [17] uses interactive manipulation of a random subset of the data to form a good query, then to apply it in batch mode to the whole dataset. 7 SUMMARY VQE combines a GQL style intentional visual query language with direct manipulation data exploration capabilities as found in systems like Visage, ....

Peter G. Selfridge, Devesh Srivastava, and Lynn O. Wilson. Idea: Interactive data exploration and analysis. In Proceedings of SIGMOD 1996, 1996.

....hands of the domain expert rather than a professional data analyst. These must thus use domain terminology. An example of general tool is Explora (Hoschka and Kl osgen 1991; Kl osgen 1996) and examples of more domain specific tools are the Interactive Data Exploration and Analysis system of AT T (Selfridge, Srivastava, and Wilson 1996), which permits one to segment market data and analyze the e#ect of new promotions and advertisements, and Advanced Scout (Bhandari et al. 1997) which seeks interesting patterns in basketball games. The promise and opportunities of data mining are obvious and commercial organizations have not ....

Selfridge, P.G., Srivastava, D., and Wilson, L.O. (1996), "IDEA: Interactive Data Exploration and Analysis," in Proceedings of SIGMOD 96,New York: ACM Press, pp. 24--34.

....platform for storing and accessing data. Our efforts for an efficient execution strategy of streams is driven by two basic ideas: query shipping and automatic usage of materializations. Instead of loading the data entirely into the system for the execution (data shipping) we use, similar to IDEA (Selfridge et al. 1996) and INLEN (Kerschberg et al. 1992) the functionality of the underlying RDBMS. For the execution, a stream is partly replaced by adequate SQL queries which can be out sourced and answered efficiently by the RDBMS. To do this, object oriented stream fractions must be mapped to relational ....

Selfridge, P.G., Srivastava, D., & Wilson, L.O. (1996). IDEA: Interactive Data Exploration and Analysis, Intl. Conf. Management of Data (SIGMOD), pp. 24-34.

....rooms) or attributes of related entities (e. g, the traffic of the street the house is located on, the crime rate of the neighborhood) In the evaluation framework I propose, the user performs such a task by using a computer environment that supports interactive data exploration and analysis (IDEA)[32, 28]. The IDEA environment provides the user with a set of powerful visualization and direct manipulation techniques that facilitate user s autonomous exploration of the set of alternatives and user s selection of a preferred alternative. When the user stops exploring the datatset, because she is ....

.... more demanding cognitive operations with fewer and more efficient perceptual and motor operations [4] Therefore, there is a growing body of research on developing Interactive Data Exploration and Analysis systems (IDEAs) in which visualization and interactive techniques play a prominent role [32, 28]. In an IDEA system, users can typically query or visualize the information at different levels of detail, and in many different formats, to search for important relationships and patterns. Furthermore, by means of interactive techniques users can control the level of detail, eliminate part of the ....

P.G. Selfridge, D. Srivastava, and L.O. Wilson. IDEA: Interactive data exploration and analysis. In Proceedings of SIGMOD-96, pages 24--34, 1996.

.... demanding cognitive operations with fewer and more efficient perceptual and motor operations (Casner 1991) Therefore, there is a growingbody of research on developing Interactive Data Exploration and Analysis systems (IDEAs) in which visualization and interactive techniques play a prominent role (Selfridge, Srivastava, Wilson 1996; Roth et al. 1997) In an IDEA system, users can typically query or visualize the information at different levels of detail, and in many different formats, to search for important relationships and patterns. Furthermore, by means of interactive techniques users can control the level of detail, ....

Selfridge, P.; Srivastava, D.; and Wilson, L. 1996. IDEA: Interactive data exploration and analysis. In Proceedings of SIGMOD-96, 24--34.

....mining system developed at AT T Laboratory by Brachman et al. 13] using sophisticated knowledge representation techniques. DataMine is system exploring interactive ad hoc query directed data mining, developed by Imielinski, et al. 45] IDEA, developed at AT T Laboratory by Selfridge, et al. [74], performs interactive data explorations and analysis. There have been many other data mining systems reported by machine learning and statistics researchers. Moreover, data warehousing systems have been seeking data mining tools for further enhancement of data analysis capabilities, and it is ....

P. G. Selfridge, D. Srivastava, and L. O. Wilson. IDEA: Interactive data exploration and analysis. In Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data, Montreal, Canada, June 1996.

.... thus between sequences of operations) In this position paper, we present the key concepts of the visual language, IDEA, that is useful in assisting the BDA in the tasks of interactive data exploration and analysis; a detailed description of the language and the implemented system is presented in [SSW96]. An IDEA program keeps track of the various actions performed by the BDA and maintains relationships between these actions; figure 1 depicts the role played by IDEA. To mitigate the problems faced by the BDA, IDEA uses a database to store not only the data but also as much information about the ....

P. G. Selfridge, D. Srivastava, and L. O. Wilson. IDEA: Interactive data exploration and analysis. In Proceedings of the ACM SIGMOD Conference on Management of Data, Montreal, Canada, 1996.

....of the data, to construct re usable IDEA programs and intuitively captures the notion of an analysis session in a form that can be run on larger data sets, shared and re used. Figure 2 illustrates a snapshot of an IDEA session. More details on the database aspects of this work can be found in [4], and more details on this work from the perspective of visual languages and knowledge discovery can be found in [5] 4. ....

P.G. Selfridge, D. Srivastava, L.O. Wilson., IDEA: Interactive Data Exploration and Analysis, accepted for presentation at SIGMOD, 1996

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P. Selfridge, D. Srivastava and L. Wilson, "IDEA: Interactive Data Exploration and Analysis", Proceedings of 25th ACM SIGMOD International Conference on Management of Data, June 1996.

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Selfridge, P.G., Srivastava, D., Wilson, L.O. (1996). IDEA: Interactive Data Exploration and Analysis, Intl. Conf. Management of Data (SIGMOD), pp. 24-34.

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Selfridge, P. G.; Srivastava, D.; and Wilson, L. O. 1996. Idea: Interactive data exploration and analysis.

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