-
Platis, N. et al.: Visualization of uncertainty in tag clouds (2016)
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- Date
- 1. 2.2016 18:25:22
- Source
- Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
-
Representation in scientific practice revisited (2014)
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- Editor
- Coopmans, C. et al.
-
Soylu, A.; Giese, M.; Jimenez-Ruiz, E.; Kharlamov, E.; Zheleznyakov, D.; Horrocks, I.: Towards exploiting query history for adaptive ontology-based visual query formulation (2014)
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- Source
- Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
-
Wu, Y.; Bai, R.: ¬An event relationship model for knowledge organization and visualization (2017)
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- Abstract
- An event is a specific occurrence involving participants, which is a typed, n-ary association of entities or other events, each identified as a participant in a specific semantic role in the event (Pyysalo et al. 2012; Linguistic Data Consortium 2005). Event types may vary across domains. Representing relationships between events can facilitate the understanding of knowledge in complex systems (such as economic systems, human body, social systems). In the simplest form, an event can be represented as Entity A <Relation> Entity B. This paper evaluates several knowledge organization and visualization models and tools, such as concept maps (Cmap), topic maps (Ontopia), network analysis models (Gephi), and ontology (Protégé), then proposes an event relationship model that aims to integrate the strengths of these models, and can represent complex knowledge expressed in events and their relationships.
-
Lin, F.-T.: Drawing a knowledge map of smart city knowledge in academia (2019)
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- Abstract
- This research takes the academic articles in the Web of Science's core collection database as a corpus to draw a series of knowledge maps, to explore the relationships, connectivity, dis-tribution, and evolution among their keywords with respect to smart cities in the last decade. Beyond just drawing a text cloud or measuring their sizes, we further explore their texture by iden-tifying the hottest keywords in academic articles, construct links between and among them that share common keywords, identify islands, rocks, reefs that are formed by connected articles-a metaphor inspired by Ong et al. (2005)-and analyze trends in their evolution. We found the following phenomena: 1) "Internet of Things" is the most frequently mentioned keyword in recent research articles; 2) the numbers of islands and reefs are increas-ing; 3) the evolutions of the numbers of weighted links have frac-tal-like structure; and, 4) the coverage of the largest rock, formed by articles that share a common keyword, in the largest island is converging into around 10% to 20%. These phenomena imply that a common interest in the technology of smart cities has been emerging among researchers. However, the administrative, social, economic, and cultural issues need more attention in academia in the future.
-
Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016)
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- Date
- 20. 1.2015 18:30:22
-
Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018)
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- Date
- 9.12.2018 16:22:25
-
Kocijan, K.: Visualizing natural language resources (2015)
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- Source
- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
-
Reiterer, H.; Jetter, H.-C.: Informationsvisualisierung (2013)
0.01
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-
Julien, C.-A.; Tirilly, P.; Dinneen, J.D.; Guastavino, C.: Reducing subject tree browsing complexity (2013)
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-
Oh, K.E.; Halpern, D.; Tremaine, M.; Chiang, J.; Silver, D.; Bemis, K.: Blocked: when the information is hidden by the visualization (2016)
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- Abstract
- This study investigated how people comprehend three-dimensional (3D) visualizations and what properties of such visualizations affect comprehension. Participants were asked to draw the face of a 3D visualization after it was cut in half. We videotaped the participants as they drew, erased, verbalized their thoughts, gestured, and moved about a two-dimensional paper presentation of the 3D visualization. The videorecords were analyzed using a grounded theory approach to generate hypotheses related to comprehension difficulties and visualization properties. Our analysis of the results uncovered three properties that made problem solving more difficult for participants. These were: (a) cuts that were at an angle in relation to at least one plane of reference, (b) nonplanar properties of the features contained in the 3D visualizations including curved layers and v-shaped layers, and (c) mixed combinations of layers. In contrast, (a) cutting planes that were perpendicular or parallel to the 3D visualization diagram's planes of reference, (b) internal features that were flat/planar, and (c) homogeneous layers were easier to comprehend. This research has direct implications for the generation and use of 3D information visualizations in that it suggests design features to include and avoid.
-
Hiniker, A.; Hong, S.R.; Kim, Y.-S.; Chen, N.-C.; West, J.D.; Aragon, C.: Toward the operationalization of visual metaphor (2017)
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-
Brockelmann, M.; Wolff, C.: 3D-Visualisierungen : Potenziale in Forschung und Lehre im Kontext von Informationswissenschaft und Medieninformatik (2013)
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-
Lamb, I.; Larson, C.: Shining a light on scientific data : building a data catalog to foster data sharing and reuse (2016)
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-
Kraker, P.; Kittel, C,; Enkhbayar, A.: Open Knowledge Maps : creating a visual interface to the world's scientific knowledge based on natural language processing (2016)
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-
Heuvel, C. van den; Salah, A.A.; Knowledge Space Lab: Visualizing universes of knowledge : design and visual analysis of the UDC (2011)
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-
Huang, S.-C.; Bias, R.G.; Schnyer, D.: How are icons processed by the brain? : Neuroimaging measures of four types of visual stimuli used in information systems (2015)
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-
Chen, R.H.-G.; Chen, C.-M.: Visualizing the world's scientific publications (2016)
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Aletras, N.; Baldwin, T.; Lau, J.H.; Stevenson, M.: Evaluating topic representations for exploring document collections (2017)
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- Abstract
- Topic models have been shown to be a useful way of representing the content of large document collections, for example, via visualization interfaces (topic browsers). These systems enable users to explore collections by way of latent topics. A standard way to represent a topic is using a term list; that is the top-n words with highest conditional probability within the topic. Other topic representations such as textual and image labels also have been proposed. However, there has been no comparison of these alternative representations. In this article, we compare 3 different topic representations in a document retrieval task. Participants were asked to retrieve relevant documents based on predefined queries within a fixed time limit, presenting topics in one of the following modalities: (a) lists of terms, (b) textual phrase labels, and (c) image labels. Results show that textual labels are easier for users to interpret than are term lists and image labels. Moreover, the precision of retrieved documents for textual and image labels is comparable to the precision achieved by representing topics using term lists, demonstrating that labeling methods are an effective alternative topic representation.
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Kraker, P.; Schramm, M.; Kittel, C.: Open knowledge maps : visuelle Literatursuche basierend auf den Prinzipien von Open Science (2019)
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