@article {931,
	title = {Visualization of Tensor Fields in Mechanics},
	journal = {Computer Graphics Forum},
	volume = {40},
	year = {2021},
	pages = {135-161},
	abstract = {Abstract Tensors are used to describe complex physical processes in many applications. Examples include the distribution of stresses in technical materials, acting forces during seismic events, or remodeling of biological tissues. While tensors encode such complex information mathematically precisely, the semantic interpretation of a tensor is challenging. Visualization can be beneficial here and is frequently used by domain experts. Typical strategies include the use of glyphs, color plots, lines, and isosurfaces. However, data complexity is nowadays accompanied by the sheer amount of data produced by large-scale simulations and adds another level of obstruction between user and data. Given the limitations of traditional methods, and the extra cognitive effort of simple methods, more advanced tensor field visualization approaches have been the focus of this work. This survey aims to provide an overview of recent research results with a strong application-oriented focus, targeting applications based on continuum mechanics, namely the fields of structural, bio-, and geomechanics. As such, the survey is complementing and extending previously published surveys. Its utility is twofold: (i) It serves as basis for the visualization community to get an overview of recent visualization techniques. (ii) It emphasizes and explains the necessity for further research for visualizations in this context.},
	keywords = {scientific visualization, Visualization},
	doi = {https://doi.org/10.1111/cgf.14209},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14209},
	author = {Hergl, Chiara and Blecha, Christian and Kretzschmar, Vanessa and Raith, Felix and G{\"u}nther, Fabian and Stommel, Markus and Jankowai, Jochen and Hotz, Ingrid and Nagel, Thomas and Scheuermann, Gerik}
}
@conference {906,
	title = {Detecting Text Reuse and Similarities between Artists in Rap Music through Visualization},
	booktitle = {LEVIA{\textquoteright}20: Leipzig Symposium on Visualization in Applications 2020},
	year = {2020},
	address = {Leipzig},
	abstract = {Detecting references and similarities in music lyrics
can be a difficult task. Crowdsourced knowledge platforms like
Genius can help in this process through user annotated
information about the artist and the song but fail to include
visualizations to help users finding similarities and structures on
a higher and more abstract level. We propose a prototype to
detect and visualize the similarity of rap artists based on their
lyrics and monolingual alignments of song lyrics. For this, we
apply word and sentence embeddings to lyrics we crawled from
Genius.},
	keywords = {Intertextuality, Text Reuse, Visualization},
	doi = {10.31219/osf.io/j4cn8},
	url = {https://osf.io/j4cn8/},
	author = {Meinecke, Christofer and J{\"a}nicke, Stefan}
}
@conference {887,
	title = {Automated Alignment of Medieval Text Versions based on Word Embeddings},
	booktitle = {LEVIA{\textquoteright}19: Leipzig Symposium on Visualization in Applications 2019},
	year = {2019},
	address = {Leipzig},
	abstract = {Medieval textuality is characterized by instability in text structure and length that varies according to the text tradition. This instability in the versions, otherwise known as {\textquotedblleft}mouvance{\textquotedblright}, is characterized by dialectal difference, traces of orality, the modification of wording and even the rewriting and rearrangement of large parts of the text. To help humanities scholars in the exploratory analysis of such complex text collections, the visual analytic system iteal was initially proposed. The system aligns similar phrases on a line-level on the basis of string similarity and word n-grams. We propose an extension of this system that replaces the parameter-based approach with an automatic one using word embeddings thereby adding a semantic component. The benefit of the new visualization system is shown through a comparison of different versions of medieval French texts. Additionally, a domain-expert compared the parameter-based approach with the approach based on word embeddings to outline the similarities and differences in the alignments.},
	keywords = {Digital Humanities, Sentence Alignment, Visualization, Word Embedding},
	doi = {10.31219/osf.io/tah3y},
	url = {https://levia19.vizcovery.de/papers/LEVIA19_paper_6.pdf},
	author = {Meinecke, Christofer and Wrisley, David Joseph and J{\"a}nicke, Stefan}
}
@article {786,
	title = {Tensor Field Visualization using Fiber Surfaces of Invariant Space},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {25},
	year = {2018},
	month = {01/2019},
	pages = {1122-1131},
	chapter = {1122},
	abstract = {Scientific visualization developed successful methods for scalar and vector fields. For tensor fields, however, effective, interactive visualizations are still missing despite progress over the last decades. We present a general approach for the generation of separating surfaces in symmetric, second-order, three-dimensional tensor fields. These surfaces are defined as fiber surfaces of the invariant space, i.e. as pre-images of surfaces in the range of a complete set of invariants. This approach leads to a generalization of the fiber surface algorithm by Klacansky et al. [16] to three dimensions in the range. This is due to the fact that the invariant space is three-dimensional for symmetric second-order tensors over a spatial domain. We present an algorithm for surface construction for simplicial grids in the domain and simplicial surfaces in the invariant space. We demonstrate our approach by applying it to stress fields from component design in mechanical engineering.},
	keywords = {fiber surface, Geometry, interaction, invariants, Mechanical engineering, Neuroscience, Strain, Tensile stress, tensor field, Visualization},
	issn = {1077-2626},
	doi = {10.1109/TVCG.2018.2864846},
	url = {https://ieeexplore.ieee.org/document/8447439},
	author = {Felix Raith and Christian Blecha and Thomas Nagel and Francesco Parisio and Olaf Kolditz and Fabian G{\"u}nther and Markus Stommel and Gerik Scheuermann}
}
@article {711,
	title = {A Decision-Support System for Sustainable Water Distribution System Planning},
	journal = {IEEE Computer Graphics and Applications},
	volume = {37},
	year = {2017},
	month = {01/2017},
	pages = {44-55},
	abstract = {An interactive decision-support system (DSS) can help experts prepare water resource management plans for decision makers and stakeholders. The design of the proposed prototype incorporates visualization techniques such as circle views, grid layout, small multiple maps, and node simplification to improve the data readability of water distribution systems. A case study with three urban water management and sanitary engineering experts revealed that the proposed DSS is satisfactory, efficient, and effective.},
	keywords = {computer graphics, Data visualization, Decision support systems, decision-support system, Image color analysis, Indexes, Layout, multiattribute visualization, network graphs, time-dependent attributes, Visualization, water resource management, Water resources},
	issn = {0272-1716},
	doi = {10.1109/MCG.2015.120 },
	url = {https://www.computer.org/csdl/mags/cg/2017/01/mcg2017010044-abs.html},
	author = {Alina Freund and Nazli Yonca Aydin and Dirk Zeckzer and Hans Hagen}
}
