A Review and Characterization of Progressive Visual Analytics
Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous i...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-07-01
|
| Series: | Informatics |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2227-9709/5/3/31 |
| _version_ | 1818531540926201856 |
|---|---|
| author | Marco Angelini Giuseppe Santucci Heidrun Schumann Hans-Jörg Schulz |
| author_facet | Marco Angelini Giuseppe Santucci Heidrun Schumann Hans-Jörg Schulz |
| author_sort | Marco Angelini |
| collection | DOAJ |
| description | Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous interaction with the emerging end result even while it is still being computed. Yet as clear-cut as this fundamental idea seems, the existing body of literature puts forth various interpretations and instantiations that have created a research domain of competing terms, various definitions, as well as long lists of practical requirements and design guidelines spread across different scientific communities. This makes it more and more difficult to get a succinct understanding of PVA’s principal concepts, let alone an overview of this increasingly diverging field. The review and discussion of PVA presented in this paper address these issues and provide (1) a literature collection on this topic, (2) a conceptual characterization of PVA, as well as (3) a consolidated set of practical recommendations for implementing and using PVA-based visual analytics solutions. |
| first_indexed | 2024-12-11T17:33:48Z |
| format | Article |
| id | doaj.art-5481098ca73a4a8cbfe9893ff96cb585 |
| institution | Directory Open Access Journal |
| issn | 2227-9709 |
| language | English |
| last_indexed | 2024-12-11T17:33:48Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj.art-5481098ca73a4a8cbfe9893ff96cb5852022-12-22T00:56:44ZengMDPI AGInformatics2227-97092018-07-01533110.3390/informatics5030031informatics5030031A Review and Characterization of Progressive Visual AnalyticsMarco Angelini0Giuseppe Santucci1Heidrun Schumann2Hans-Jörg Schulz3Sapienza University of Rome, 00185 Rome, ItalySapienza University of Rome, 00185 Rome, ItalyUniversity of Rostock, 18059 Rostock, GermanyAarhus University, 8000 Aarhus Aarhus, DenmarkProgressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous interaction with the emerging end result even while it is still being computed. Yet as clear-cut as this fundamental idea seems, the existing body of literature puts forth various interpretations and instantiations that have created a research domain of competing terms, various definitions, as well as long lists of practical requirements and design guidelines spread across different scientific communities. This makes it more and more difficult to get a succinct understanding of PVA’s principal concepts, let alone an overview of this increasingly diverging field. The review and discussion of PVA presented in this paper address these issues and provide (1) a literature collection on this topic, (2) a conceptual characterization of PVA, as well as (3) a consolidated set of practical recommendations for implementing and using PVA-based visual analytics solutions.http://www.mdpi.com/2227-9709/5/3/31visual analyticsprogressive visualizationincremental visualizationonline algorithms |
| spellingShingle | Marco Angelini Giuseppe Santucci Heidrun Schumann Hans-Jörg Schulz A Review and Characterization of Progressive Visual Analytics Informatics visual analytics progressive visualization incremental visualization online algorithms |
| title | A Review and Characterization of Progressive Visual Analytics |
| title_full | A Review and Characterization of Progressive Visual Analytics |
| title_fullStr | A Review and Characterization of Progressive Visual Analytics |
| title_full_unstemmed | A Review and Characterization of Progressive Visual Analytics |
| title_short | A Review and Characterization of Progressive Visual Analytics |
| title_sort | review and characterization of progressive visual analytics |
| topic | visual analytics progressive visualization incremental visualization online algorithms |
| url | http://www.mdpi.com/2227-9709/5/3/31 |
| work_keys_str_mv | AT marcoangelini areviewandcharacterizationofprogressivevisualanalytics AT giuseppesantucci areviewandcharacterizationofprogressivevisualanalytics AT heidrunschumann areviewandcharacterizationofprogressivevisualanalytics AT hansjorgschulz areviewandcharacterizationofprogressivevisualanalytics AT marcoangelini reviewandcharacterizationofprogressivevisualanalytics AT giuseppesantucci reviewandcharacterizationofprogressivevisualanalytics AT heidrunschumann reviewandcharacterizationofprogressivevisualanalytics AT hansjorgschulz reviewandcharacterizationofprogressivevisualanalytics |