Supporting Data Analysis Through Visualizations

نویسندگان

  • Paolo Buono
  • Maria Francesca Costabile
  • Francesca A. Lisi
چکیده

Information visualization is a process that transforms information into a visual form, thus enabling the user to observe it. By graphically presenting data, the user may discover new and useful properties, their correlations, and also detect possible deviations from the expected values. In this paper, after discussing some ideas about possible fruitful use of visualization for data mining, we present a visualization module we are developing in the context of a project funded by the European Union. The project aims at offering on-line innovative services to support the business processes of trade fairs, both real and/or Web-based virtual fair. This module generates data visualizations on the WWW, which are exploited to facilitate human-computer interaction, to allow easy access to the stored data, and to present the retrieved information in appropriate ways, thus helping users in their data analysis activities.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Can Physical Visualizations Support Analytical Tasks?

While physical objects have been used to represent information for a long time, physical visualizations only recently started to attract attention from the InfoVis and HCI communities. In this article we present our early experiments in designing physical visualizations for supporting data analysis. Based on Amar’s taxonomy of analytical tasks [1] we show that physical visualizations can suppor...

متن کامل

SEEDB: Supporting Visual Analytics with Data-Driven Recommendations

Data analysts often build visualizations as the first step in their analytical workflow. However, when working with high-dimensional datasets, identifying visualizations that show relevant or desired trends in data can be laborious. We propose SEEDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SEEDB intelligently explores the s...

متن کامل

LinkDaViz - Automatic Binding of Linked Data to Visualizations

As the Web of Data is growing steadily, the demand for userfriendly means for exploring, analyzing and visualizing Linked Data is also increasing. The key challenge for visualizing Linked Data consists in providing a clear overview of the data and supporting non-technical users in finding suitable visualizations while hiding technical details of Linked Data and visualization configuration. In o...

متن کامل

Supporting Network Management through Declaratively Specified Data Visualizations

The complexity of managing and controlling large heterogeneous networks requires the availability of management stations equipped with sophisticated tools. A fundamental feature of an advanced network management station is the capability to present to the human manager a comprehensible picture of the relevant scenarios. The tools present at the station must allow the manager specify management ...

متن کامل

Supporting Network Management through Declaratively Speciied Data Visualizations

The complexity of managing and controlling large heterogeneous networks requires the availability of management stations equipped with sophisticated tools. A fundamental feature of an advanced network management station is the capability to present to the human manager a comprehensible picture of the relevant scenarios. The tools present at the station must allow the manager specify management ...

متن کامل

SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics

Data analysts often build visualizations as the first step in their analytical workflow. However, when working with high-dimensional datasets, identifying visualizations that show relevant or desired trends in data can be laborious. We propose SeeDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SeeDB intelligently explores the s...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001