PrAVA: Preprocessing profiling approach for visual analytics. (July 2021)
- Record Type:
- Journal Article
- Title:
- PrAVA: Preprocessing profiling approach for visual analytics. (July 2021)
- Main Title:
- PrAVA: Preprocessing profiling approach for visual analytics
- Authors:
- Milani, Alessandra Maciel Paz
Loges, Lucas Angelo
Paulovich, Fernando Vieira
Manssour, Isabel Harb - Abstract:
- To accommodate the demands of a data-driven society, we have expanded our ability to collect and store data, develop sophisticated algorithms, and generate elaborated visual representations of the data analysis process outcomes. However, data preprocessing, as the activity of transforming the raw data into an appropriate format for subsequent analysis, is still a challenging part of this process. Although we can find studies that address the use of visualization techniques to support the activities in the scope of preprocessing, the current Visual Analytics processes do not consider preprocessing an equally important phase in their processes. Hence, with this paper, we aim to contribute to the discussion of how we can incorporate the preprocessing as a prominent phase in the Visual Analytics process and promote better alternatives to assist the data analysts during the preprocessing activities. To achieve that, we are introducing the Preprocessing Profiling Approach for Visual Analytics (PrAVA), a conceptual Visual Analytics process that includes Preprocessing Profiling as a new phase. It also contemplates a set of guidelines to be considered by new solutions adopting PrAVA. Moreover, we analyze its applicability through use case scenarios that show resourceful methods for data understanding and evaluation of the preprocessing impacts. As a final contribution, we indicate a list of research opportunities in the scope of preprocessing combined with visualization and VisualTo accommodate the demands of a data-driven society, we have expanded our ability to collect and store data, develop sophisticated algorithms, and generate elaborated visual representations of the data analysis process outcomes. However, data preprocessing, as the activity of transforming the raw data into an appropriate format for subsequent analysis, is still a challenging part of this process. Although we can find studies that address the use of visualization techniques to support the activities in the scope of preprocessing, the current Visual Analytics processes do not consider preprocessing an equally important phase in their processes. Hence, with this paper, we aim to contribute to the discussion of how we can incorporate the preprocessing as a prominent phase in the Visual Analytics process and promote better alternatives to assist the data analysts during the preprocessing activities. To achieve that, we are introducing the Preprocessing Profiling Approach for Visual Analytics (PrAVA), a conceptual Visual Analytics process that includes Preprocessing Profiling as a new phase. It also contemplates a set of guidelines to be considered by new solutions adopting PrAVA. Moreover, we analyze its applicability through use case scenarios that show resourceful methods for data understanding and evaluation of the preprocessing impacts. As a final contribution, we indicate a list of research opportunities in the scope of preprocessing combined with visualization and Visual Analytics to stimulate a shift to visual preprocessing. … (more)
- Is Part Of:
- Information visualization. Volume 20:Number 2/3(2021)
- Journal:
- Information visualization
- Issue:
- Volume 20:Number 2/3(2021)
- Issue Display:
- Volume 20, Issue 2/3 (2021)
- Year:
- 2021
- Volume:
- 20
- Issue:
- 2/3
- Issue Sort Value:
- 2021-0020-NaN-0000
- Page Start:
- 101
- Page End:
- 122
- Publication Date:
- 2021-07
- Subjects:
- Information visualization -- visual analytics -- preprocessing -- data preparation profiling
Information visualization -- Periodicals
006.605 - Journal URLs:
- http://ivi.sagepub.com/ ↗
http://www.palgrave-journals.com/ivs/index.html ↗
http://www.uk.sagepub.com ↗ - DOI:
- 10.1177/14738716211021591 ↗
- Languages:
- English
- ISSNs:
- 1473-8716
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.401000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16704.xml