Visualizing Cooperative Activities with Ellimaps: The Case of Wikipedia

Otjacques, Benoît; Cornil, Maël; Feltz, Fernand

doi:10.1007/978-3-642-04265-2_6

Cited by 5 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, if a text were mostly low quality, the system would determine it to be low quality for demanding users but high quality for undemanding users. Holloway et al [23] and Otjacques et al [24] have already discussed the user interface of Wikipedia before. Therefore, we should develop a user interface that is useful for every user.…”

Section: Resultsmentioning

confidence: 98%

Mutual evaluation of editors and texts for assessing quality of Wikipedia articles

Suzuki

Yoshikawa

2012

Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration

View full text Add to dashboard Cite

In this paper, we propose a method to identify good quality Wikipedia articles by mutually evaluating editors and texts. A major approach for assessing article quality is a text survival ratio based approach. In this approach, when a text survives beyond multiple edits, the text is assessed as good quality. This approach assumes that poor quality texts are deleted by editors with high possibility. However, many vandals delete good quality texts frequently, then the survival ratios of good quality texts are improperly decreased by vandals. As a result, many good quality texts are unfairly assessed as poor quality. In our method, we consider editor quality for calculating text quality, and decrease the impacts on text qualities by the vandals who has low quality. Using this improvement, the accuracy of the text quality should be improved. However, an inherent problem of this idea is that the editor qualities are calculated by the text qualities. To solve this problem, we mutually calculate the editor and text qualities until they converge. We did our experimental evaluation, and we confirmed that the proposed method could accurately assess the text qualities.

show abstract

Section: Resultsmentioning

confidence: 98%

Mutual evaluation of editors and texts for assessing quality of Wikipedia articles

Suzuki

Yoshikawa

2012

Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration

View full text Add to dashboard Cite

show abstract

“…Treemap has been extensively used to visualise intrinsically hierarchical data [17], [18], providing an overview of an entire dataset at a glance. Ellimap [19] is another type of 2D space-filling visualisation approach, which uses ellipses instead of rectangles to represent the nodes. Usually, shapes of 2D space filling visualisations are area proportional to a given metric (e.g., the number of items), visually giving an overview on this value.…”

Section: Related Workmentioning

confidence: 99%

“…The same tool tip box could be used to show additional statistical information (such as the average, minimum and maximum drag-coefficient Cx values), as suggested by users during the Usability Study (Section V). ExploraTool tries to exploit all of the available screen space using ellimap [19]. Each group of simulations is a set depicted by an ellipse.…”

Section: A Data Set Overviewmentioning

confidence: 99%

“…The use of ellipses as basic shapes guarantees there will be space between sibling ellipses at same level and amongst nested ellipses. This extra space improves the hierarchy discernment [19] and every operation involves exactly the target shape. For instance, in order to drill down in the hierarchy, the user points and clicks on exactly the nested ellipse required.…”

Section: B Data Set Explorationmentioning

confidence: 99%

See 1 more Smart Citation

Visual Exploration System in an Industrial Context

Fish

Gargiulo

Malandrino

et al. 2016

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

Abstract-This paper describes ExploraTool a new interactive tool to visually explore data from multiple repositories. The tool has been applied in a real setting to explore CFD simulation data and obtain new insights into the space of simulations. The inclusion of free exploration, filtering operations and chart generation provides a quick method for performance comparisons. The paper proposes an algorithmic means of processing input in the form of tabular data sets, generating a plausible hierarchical structure over metadata categories which is used to initialize the visualisation together with interactions methods to explore, select and compare sets of simulation data. This paper also reports on the Evaluation Study performed involving 24 engineers over two distinct locations from a large automotive manufacturer, to evaluate the usability and the overall user satisfaction with the tool. Participants rated the tool as intuitive, useful and effective.

show abstract

“…Tremendous text contents have been created by users, and also been visualized for various research purposes. Due to its popularity and availability of data, text contents of Wikipedia attract many visualization studies [13][14][15][16][17][18][19][20]. While some of these studies focused on the metadata of Wikipedia entries, such as authors [18][19][20] and editing frequencies [13], a few traced the revision history of text contents [15,16].…”

Section: User-generated Text Contentsmentioning

confidence: 99%

SDSS Log Viewer : visual exploratory analysis of large-volume SQL log data

Zhang

Chen

Vogeley

et al. 2012

Visualization and Data Analysis 2012

View full text Add to dashboard Cite

User-generated Structured Query Language (SQL) queries are a rich source of information for database analysts, information scientists, and the end users of databases. In this study a group of scientists in astronomy and computer and information scientists work together to analyze a large volume of SQL log data generated by users of the Sloan Digital Sky Survey (SDSS) data archive in order to better understand users' data seeking behavior. While statistical analysis of such logs is useful at aggregated levels, efficiently exploring specific patterns of queries is often a challenging task due to the typically large volume of the data, multivariate features, and data requirements specified in SQL queries. To enable and facilitate effective and efficient exploration of the SDSS log data, we designed an interactive visualization tool, called the SDSS Log Viewer, which integrates time series visualization, text visualization, and dynamic query techniques. We describe two analysis scenarios of visual exploration of SDSS log data, including understanding unusually high daily query traffic and modeling the types of data seeking behaviors of massive query generators. The two scenarios demonstrate that the SDSS Log Viewer provides a novel and potentially valuable approach to support these targeted tasks.Keywords: SQL log analysis, visual exploratory analysis, multivariate data, text visualization, multiple views INTRODUCTIONUser-generated Structured Query Language (SQL) query logs are common in science, business, engineering, and many other domains. These logs contain information about users' data seeking behavior and system performance, and thus are rich information sources for analysts such as database administrators, system designers, and user behavior researchers. Like normal transaction logs, SQL logs can be characterized as multivariate, temporal, and categorical event sequences. On the other hand, SQL logs have their own distinct feature: semi-structured and often complex queries generated by users. While statistical methods such as analytical functions offered by database systems can reveal query patterns at aggregated levels, quickly exploring SQL logs in detail is often challenging because of the typically large volume of log data, multivariate features, and text content of queries. In this paper we, a group of information scientists collaborated with a group of data scientists of the Sloan Digital Sky Survey (SDSS), work together to design and develop an interactive visualization tool, called the SDSS Log Viewer, which enables and facilitates visual exploration of the SQL log data generated by users of SDSS data archive. By integrating time series visualization, text visualization, and dynamic query techniques, the tool helps SDSS data analysts to quickly identify massive query generators and reveal their data seeking models. Although this is a domain-specific case study, the method and experience of this study can be generalized for similar datasets to discover patterns and relationships between log features and...

show abstract

Visualizing Cooperative Activities with Ellimaps: The Case of Wikipedia

Cited by 5 publications

References 13 publications

Mutual evaluation of editors and texts for assessing quality of Wikipedia articles

Mutual evaluation of editors and texts for assessing quality of Wikipedia articles

Visual Exploration System in an Industrial Context

SDSS Log Viewer : visual exploratory analysis of large-volume SQL log data

Contact Info

Product

Resources

About