11 Search Results for "Ebert, David S."


Document
Climate Change: What is Computing’s Responsibility? (Dagstuhl Perspectives Workshop 25122)

Authors: Bran Knowles, Vicki L. Hanson, Christoph Becker, Mike Berners-Lee, Andrew A. Chien, Benoit Combemale, Vlad Coroamă, Koen De Bosschere, Yi Ding, Adrian Friday, Boris Gamazaychikov, Lynda Hardman, Simon Hinterholzer, Mattias Höjer, Lynn Kaack, Lenneke Kuijer, Anne-Laure Ligozat, Jan Tobias Muehlberg, Yunmook Nah, Thomas Olsson, Anne-Cécile Orgerie, Daniel Pargman, Birgit Penzenstadler, Tom Romanoff, Emma Strubell, Colin Venters, and Junhua Zhao

Published in: Dagstuhl Manifestos, Volume 11, Issue 1 (2025)


Abstract
This Manifesto was produced from the Perspectives Workshop 25122 entitled "Climate Change: What is Computing’s Responsibility?" held March 16-19, 2025 at Schloss Dagstuhl, Germany. The Workshop provided a forum for world-leading computer scientists and expert consultants on environmental policy and sustainable transition to engage in a critical and urgent conversation about computing’s responsibilities in addressing climate change - or more aptly, climate crisis. The resulting Manifesto outlines commitments and directions for future action which, if adopted as a basis for more responsible computing practices, will help ensure that these technologies do not threaten the long-term habitability of the planet. We preface our Manifesto with a recognition that humanity is on a path that is not in agreement with international global warming targets and explore how computing technologies are currently hastening the overshoot of these boundaries. We critically assess the vaunted potential for harnessing computing technologies for the mitigation of global warming, agreeing that, under current circumstances, computing is contributing to negative environmental impacts in other sectors. Computing primarily improves efficiency and reduces costs which leads to more consumption and more negative environmental impact. Relying solely on efficiency gains in computing has thus far proven to be insufficient to curb global greenhouse gas emissions. Therefore, computing’s purpose within a strategy for tackling climate change must be reimagined. Our recommendations cover changes that need to be urgently made to the design priorities of computing technologies, but also speak to the more systemic shift in mindset, with sustainability and human rights providing a necessary moral foundation for developing the kinds of computing technologies most needed by society. We also stress the importance of digital policy that accounts for both the direct material impacts of computing and the detrimental indirect impacts arising from computing-enabled efficiencies, and the role of computing professionals in informing policy making.

Cite as

Bran Knowles, Vicki L. Hanson, Christoph Becker, Mike Berners-Lee, Andrew A. Chien, Benoit Combemale, Vlad Coroamă, Koen De Bosschere, Yi Ding, Adrian Friday, Boris Gamazaychikov, Lynda Hardman, Simon Hinterholzer, Mattias Höjer, Lynn Kaack, Lenneke Kuijer, Anne-Laure Ligozat, Jan Tobias Muehlberg, Yunmook Nah, Thomas Olsson, Anne-Cécile Orgerie, Daniel Pargman, Birgit Penzenstadler, Tom Romanoff, Emma Strubell, Colin Venters, and Junhua Zhao. Climate Change: What is Computing’s Responsibility? (Dagstuhl Perspectives Workshop 25122). In Dagstuhl Manifestos, Volume 11, Issue 1, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@Article{knowles_et_al:DagMan.11.1.1,
  author =	{Knowles, Bran and Hanson, Vicki L. and Becker, Christoph and Berners-Lee, Mike and Chien, Andrew A. and Combemale, Benoit and Coroam\u{a}, Vlad and De Bosschere, Koen and Ding, Yi and Friday, Adrian and Gamazaychikov, Boris and Hardman, Lynda and Hinterholzer, Simon and H\"{o}jer, Mattias and Kaack, Lynn and Kuijer, Lenneke and Ligozat, Anne-Laure and Muehlberg, Jan Tobias and Nah, Yunmook and Olsson, Thomas and Orgerie, Anne-C\'{e}cile and Pargman, Daniel and Penzenstadler, Birgit and Romanoff, Tom and Strubell, Emma and Venters, Colin and Zhao, Junhua},
  title =	{{Climate Change: What is Computing’s Responsibility? (Dagstuhl Perspectives Workshop 25122)}},
  pages =	{1--18},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2025},
  volume =	{11},
  number =	{1},
  editor =	{Knowles, Bran and Hanson, Vicki L. and Becker, Christoph and Berners-Lee, Mike and Chien, Andrew A. and Combemale, Benoit and Coroam\u{a}, Vlad and De Bosschere, Koen and Ding, Yi and Friday, Adrian and Gamazaychikov, Boris and Hardman, Lynda and Hinterholzer, Simon and H\"{o}jer, Mattias and Kaack, Lynn and Kuijer, Lenneke and Ligozat, Anne-Laure and Muehlberg, Jan Tobias and Nah, Yunmook and Olsson, Thomas and Orgerie, Anne-C\'{e}cile and Pargman, Daniel and Penzenstadler, Birgit and Romanoff, Tom and Strubell, Emma and Venters, Colin and Zhao, Junhua},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.11.1.1},
  URN =		{urn:nbn:de:0030-drops-250724},
  doi =		{10.4230/DagMan.11.1.1},
  annote =	{Keywords: sustainability, climate change, efficiency, supply chain management, climate modelling}
}
Document
DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs

Authors: Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)


Abstract
Determining the distance between two loci within a genomic region is a recurrent operation in various tasks in computational genomics. A notable example of this task arises in paired-end read mapping as a form of validation of distances between multiple alignments. While straightforward for a single genome, graph-based reference structures render the operation considerably more involved. Given the sheer number of such queries in a typical read mapping experiment, an efficient algorithm for answering distance queries is crucial. In this paper, we introduce DiVerG, a compact data structure as well as a fast and scalable algorithm, for constructing distance indexes for general sequence graphs on multi-core CPU and many-core GPU architectures. DiVerG is based on PairG [Jain et al., 2019], but overcomes the limitations of PairG by exploiting the extensive potential for improvements in terms of scalability and space efficiency. As a consequence, DiVerG can process substantially larger datasets, such as whole human genomes, which are unmanageable by PairG. DiVerG offers faster index construction time and consistently faster query time with gains proportional to the size of the underlying compact data structure. We demonstrate that our method performs favorably on multiple real datasets at various scales. DiVerG achieves superior performance over PairG; e.g. resulting to 2.5-4x speed-up in query time, 44-340x smaller index size, and 3-50x faster construction time for the genome graph of the MHC region, as a particularly variable region of the human genome. The implementation is available at: https://github.com/cartoonist/diverg

Cite as

Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall. DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 10:1-10:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{ghaffaari_et_al:LIPIcs.WABI.2025.10,
  author =	{Ghaffaari, Ali and Sch\"{o}nhuth, Alexander and Marschall, Tobias},
  title =	{{DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{10:1--10:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.10},
  URN =		{urn:nbn:de:0030-drops-239369},
  doi =		{10.4230/LIPIcs.WABI.2025.10},
  annote =	{Keywords: Sequence graph, distance index, read mapping, sparse matrix}
}
Document
Human Readable Compression of GFA Paths Using Grammar-Based Code

Authors: Peter Heringer and Daniel Doerr

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)


Abstract
Pangenome graphs offer a compact and comprehensive representation of genomic diversity, improving tasks such as variant calling, genotyping, and other downstream analyses. Although the underlying graph structures scale sublinearly with the number of haplotypes, the widely used GFA file format suffers from rapidly growing file sizes due to the explicit and repetitive encoding of haplotype paths. In this work, we introduce an extension to the GFA format that enables efficient grammar-based compression of haplotype paths while retaining human readability. In addition, grammar-based encoding provides an efficient in-memory data structure that does not require decompression, but conversely improves the runtime of many computational tasks that involve haplotype comparisons. We present sqz, a method that makes use of the proposed format extension to encode haplotype paths using byte pair encoding, a grammar-based compression scheme. We evaluate sqz on recent human pangenome graphs from Heumos et al. and the Human Pangenome Reference Consortium (HPRC), comparing it to existing compressors bgzip, gbz, and sequitur. sqz scales sublinearly with the number of haplotypes in a pangenome graph and consistently achieves higher compression ratios than sequitur and up to 5 times better compression than bgzip in HPRC graphs and up to 10 times in the graph from Heumos et al.. When combined with bgzip, sqz matches or excels the compression ratio of gbz across all our datasets. These results demonstrate the potential of our proposed extension of the GFA format in reducing haplotype path redundancy and improving storage efficiency for pangenome graphs.

Cite as

Peter Heringer and Daniel Doerr. Human Readable Compression of GFA Paths Using Grammar-Based Code. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 14:1-14:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{heringer_et_al:LIPIcs.WABI.2025.14,
  author =	{Heringer, Peter and Doerr, Daniel},
  title =	{{Human Readable Compression of GFA Paths Using Grammar-Based Code}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{14:1--14:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.14},
  URN =		{urn:nbn:de:0030-drops-239395},
  doi =		{10.4230/LIPIcs.WABI.2025.14},
  annote =	{Keywords: pangenomics, pangenome graphs, compression, grammar-based code, byte pair encoding}
}
Document
Phasing Data from Genotype Queries via the μ-PBWT

Authors: Davide Cozzi, Paola Bonizzoni, Christina Boucher, Ben Langmead, and Yuri Pirola

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)


Abstract
Genotype phasing - the process of reconstructing haplotypes from genotype data - is a fundamental problem in genomics with applications in ancestry inference, imputation, and disease association. Traditional phasing methods rely on statistical models or combinatorial approaches which can be computationally expensive, particularly when applied to large-scale reference panels. In this paper, we present a first exploration of using the μ-PBWT (a run-length encoded Positional Burrows-Wheeler Transform) to solve the genotype phasing problem with a reference panel. Leveraging our previous results on positional substrings, we propose an approach that can explain a query genotype if the corresponding haplotype pair exists in the input panel. Moreover, our method is extended to cases where such a pair does not exist, even though some regions should remain unphased if they cannot be explicitly explained using the reference panel. We implemented this method and compared it against Beagle, a state-of-the-art phasing tool, demonstrating that, in the absence of mutations and recombinations, our approach correctly identifies the haplotype pair that explains a genotype query while using seven times less memory than Beagle. However, we also observe that as mutation rates increase, the quality of the phasing decreases as a result of the growing difficulty of identifying consistent haplotype pairs in the presence of sequence variation. These findings highlight the potential of μ-PBWT as an efficient alternative for genotype phasing, particularly in settings where computational resources are limited. The source code is publicly available at https://github.com/dlcgold/muPBWT/tree/phase.

Cite as

Davide Cozzi, Paola Bonizzoni, Christina Boucher, Ben Langmead, and Yuri Pirola. Phasing Data from Genotype Queries via the μ-PBWT. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 10:1-10:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{cozzi_et_al:OASIcs.Manzini.10,
  author =	{Cozzi, Davide and Bonizzoni, Paola and Boucher, Christina and Langmead, Ben and Pirola, Yuri},
  title =	{{Phasing Data from Genotype Queries via the \mu-PBWT}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{10:1--10:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.10},
  URN =		{urn:nbn:de:0030-drops-239183},
  doi =		{10.4230/OASIcs.Manzini.10},
  annote =	{Keywords: Positional Burrows-Wheeler Transform, r-index, minimal position substring cover, set-maximal exact matches, genotype phasing}
}
Document
Resource Paper
Whelk: An OWL EL+RL Reasoner Enabling New Use Cases

Authors: James P. Balhoff and Christopher J. Mungall

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2


Abstract
Many tasks in the biosciences rely on reasoning with large OWL terminologies (Tboxes), often combined with even larger databases. In particular, a common task is retrieval queries that utilize relational expressions; for example, “find all genes expressed in the brain or any part of the brain”. Automated reasoning on these ontologies typically relies on scalable reasoners targeting the EL subset of OWL, such as ELK. While the introduction of ELK has been transformative in the incorporation of reasoning into bio-ontology quality control and production pipelines, we have encountered limitations when applying it to use cases involving high throughput query answering or reasoning about datasets describing instances (Aboxes). Whelk is a fast OWL reasoner for combined EL+RL reasoning. As such, it is particularly useful for many biological ontology tasks, particularly those characterized by large Tboxes using the EL subset of OWL, combined with Aboxes targeting the RL subset of OWL. Whelk is implemented in Scala and utilizes immutable functional data structures, which provides advantages when performing incremental or dynamic reasoning tasks. Whelk supports querying complex class expressions at a substantially greater rate than ELK, and can answer queries or perform incremental reasoning tasks in parallel, enabling novel applications of OWL reasoning.

Cite as

James P. Balhoff and Christopher J. Mungall. Whelk: An OWL EL+RL Reasoner Enabling New Use Cases. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 7:1-7:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{balhoff_et_al:TGDK.2.2.7,
  author =	{Balhoff, James P. and Mungall, Christopher J.},
  title =	{{Whelk: An OWL EL+RL Reasoner Enabling New Use Cases}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{7:1--7:17},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.7},
  URN =		{urn:nbn:de:0030-drops-225918},
  doi =		{10.4230/TGDK.2.2.7},
  annote =	{Keywords: Web Ontology Language, OWL, Semantic Web, ontology, reasoner}
}
Document
Position
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Authors: Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1


Abstract
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.

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Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 5:1-5:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@Article{chen_et_al:TGDK.1.1.5,
  author =	{Chen, Jiaoyan and Dong, Hang and Hastings, Janna and Jim\'{e}nez-Ruiz, Ernesto and L\'{o}pez, Vanessa and Monnin, Pierre and Pesquita, Catia and \v{S}koda, Petr and Tamma, Valentina},
  title =	{{Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:33},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.5},
  URN =		{urn:nbn:de:0030-drops-194791},
  doi =		{10.4230/TGDK.1.1.5},
  annote =	{Keywords: Knowledge graphs, Life science, Knowledge discovery, Explainable AI}
}
Document
Interaction with Information for Visual Reasoning (Dagstuhl Seminar 13352)

Authors: David S. Ebert, Brian D. Fisher, and Petra Isenberg

Published in: Dagstuhl Reports, Volume 3, Issue 8 (2013)


Abstract
From August 26--August 30, 2013 Seminar 13352 was held at Dagstuhl on the topic of "Interaction with Information for Visual Reasoning." The seminar brought together a group of cognitive scientists, psychologists, and computer scientists in the area of scientific visualization, information visualization, and visual analytics who were carefully selected for their theoretical and methodological capabilities and history of interdisciplinary collaboration. During the workshop seven discussion groups were formed during which the role of interaction for visualization was carefully reflected on. We discussed in particular the value, structure, and different types of interaction but also how to evaluate visualization and the idea of 'narrative' as applied to visual analytics. This report documents the program and short summaries of the discussion groups for the seminar.

Cite as

David S. Ebert, Brian D. Fisher, and Petra Isenberg. Interaction with Information for Visual Reasoning (Dagstuhl Seminar 13352). In Dagstuhl Reports, Volume 3, Issue 8, pp. 151-167, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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@Article{ebert_et_al:DagRep.3.8.151,
  author =	{Ebert, David S. and Fisher, Brian D. and Isenberg, Petra},
  title =	{{Interaction with Information for Visual Reasoning (Dagstuhl Seminar 13352)}},
  pages =	{151--167},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2013},
  volume =	{3},
  number =	{8},
  editor =	{Ebert, David S. and Fisher, Brian D. and Isenberg, Petra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.3.8.151},
  URN =		{urn:nbn:de:0030-drops-43463},
  doi =		{10.4230/DagRep.3.8.151},
  annote =	{Keywords: Interaction, visualization, visual analytics, cognitive science, psychology}
}
Document
Abstract Feature Space Representation for Volumetric Transfer Function Exploration

Authors: Ross Maciejewski, Yun Jang, David S. Ebert, and Kelly P. Gaither

Published in: Dagstuhl Follow-Ups, Volume 2, Scientific Visualization: Interactions, Features, Metaphors (2011)


Abstract
The application of n-dimensional transfer functions for feature segmentation has become increasingly popular in volume rendering. Recent work has focused on the utilization of higher order dimensional transfer functions incorporating spatial dimensions (x,y, and z) along with traditional feature space dimensions (value and value gradient). However, as the dimensionality increases, it becomes exceedingly difficult to abstract the transfer function into an intuitive and interactive workspace. In this work we focus on populating the traditional two-dimensional histogram with a set of derived metrics from the spatial (x, y and z) and feature space (value, value gradient, etc.) domain to create a set of abstract feature space transfer function domains. Current two-dimensional transfer function widgets typically consist of a two-dimensional histogram where each entry in the histogram represents the number of voxels that maps to that entry. In the case of an abstract transfer function design, the amount of spatial variance at that histogram coordinate is mapped instead, thereby relating additional information about the data abstraction in the projected space. Finally, a non-parametric kernel density estimation approach for feature space clustering is applied in the abstracted space, and the resultant transfer functions are discussed with respect to the space abstraction.

Cite as

Ross Maciejewski, Yun Jang, David S. Ebert, and Kelly P. Gaither. Abstract Feature Space Representation for Volumetric Transfer Function Exploration. In Scientific Visualization: Interactions, Features, Metaphors. Dagstuhl Follow-Ups, Volume 2, pp. 212-221, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InCollection{maciejewski_et_al:DFU.Vol2.SciViz.2011.212,
  author =	{Maciejewski, Ross and Jang, Yun and Ebert, David S. and Gaither, Kelly P.},
  title =	{{Abstract Feature Space Representation for Volumetric Transfer Function Exploration}},
  booktitle =	{Scientific Visualization: Interactions, Features, Metaphors},
  pages =	{212--221},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-26-2},
  ISSN =	{1868-8977},
  year =	{2011},
  volume =	{2},
  editor =	{Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol2.SciViz.2011.212},
  URN =		{urn:nbn:de:0030-drops-32955},
  doi =		{10.4230/DFU.Vol2.SciViz.2011.212},
  annote =	{Keywords: Volumetric Transfer Function, Abstract Feature Space}
}
Document
09251 Abstracts Collection – Scientific Visualization

Authors: David S. Ebert, Eduard Gröller, Hans Hagen, and Arie Kaufman

Published in: Dagstuhl Seminar Proceedings, Volume 9251, Scientific Visualization (2010)


Abstract
From 06-14-2009 to 06-19-2009, the Dagstuhl Seminar 09251 ``Scientific Visualization '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, over 50 international participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general.

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David S. Ebert, Eduard Gröller, Hans Hagen, and Arie Kaufman. 09251 Abstracts Collection – Scientific Visualization. In Scientific Visualization. Dagstuhl Seminar Proceedings, Volume 9251, pp. 1-36, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{ebert_et_al:DagSemProc.09251.1,
  author =	{Ebert, David S. and Gr\"{o}ller, Eduard and Hagen, Hans and Kaufman, Arie},
  title =	{{09251 Abstracts Collection – Scientific Visualization}},
  booktitle =	{Scientific Visualization},
  pages =	{1--36},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9251},
  editor =	{David S. Ebert and Eduard Gr\"{o}ller and Hans Hagen and Arie Kaufman},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09251.1},
  URN =		{urn:nbn:de:0030-drops-27436},
  doi =		{10.4230/DagSemProc.09251.1},
  annote =	{Keywords: Scientific visualization, Data analysis, Data modeling, Segmentation, Knowledge extraction, Ubiquitous visualization, Categorical visualization, Intelligent/automatic visualization, Point-based/mesh-free visualization}
}
Document
07291 Abstracts Collection – Scientific Visualization

Authors: David S. Ebert, Hans Hagen, Kenneth I. Joy, and Daniel A. Keim

Published in: Dagstuhl Seminar Proceedings, Volume 7291, Scientific Visualization (2008)


Abstract
From 15.07. to 20.07.07, the Dagstuhl Seminar 07291 ``Scientific Visualization'' was held in the International Conference and Research Center (IBFI),Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

Cite as

David S. Ebert, Hans Hagen, Kenneth I. Joy, and Daniel A. Keim. 07291 Abstracts Collection – Scientific Visualization. In Scientific Visualization. Dagstuhl Seminar Proceedings, Volume 7291, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)


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@InProceedings{ebert_et_al:DagSemProc.07291.1,
  author =	{Ebert, David S. and Hagen, Hans and Joy, Kenneth I. and Keim, Daniel A.},
  title =	{{07291 Abstracts Collection – Scientific Visualization}},
  booktitle =	{Scientific Visualization},
  pages =	{1--18},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{7291},
  editor =	{David S. Ebert and Hans Hagen and Kenneth I. Joy and Daniel A. Keim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07291.1},
  URN =		{urn:nbn:de:0030-drops-14145},
  doi =		{10.4230/DagSemProc.07291.1},
  annote =	{Keywords: Markov chains, numerical methods, web information retrieval, performance evaluation, intrusion detection, aggregation-disaggregation methods, graph-oriented decomposition}
}
Document
07291 Summary – Scientific Visualization

Authors: David S. Ebert, Hans Hagen, Kenneth I. Joy, and Daniel A. Keim

Published in: Dagstuhl Seminar Proceedings, Volume 7291, Scientific Visualization (2008)


Abstract
Scientific visualization (SV) is concerned with the use of computer-generated images to aid the understanding, analysis and manipulation of data. Since its beginning in the early 90's, the techniques of SV have aided scientists, engineers, medical practitioners, and others in the study of a wide variety of data sets including, for example, high performance computing simulations, measured data from scanners (CAT, MR, confocal microscopy), internet traffic, and financial records. One of the important themes being nurtured under the aegis of Scientific Visualization is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes and simulations involving voluminous data sets across diverse scientific disciplines. Since vision dominates our sensory input, strong efforts have been made to bring the mathematical abstraction and modeling to our eyes through the mediation of computer graphics. This interplay between various application areas and their specific problem solving visualization techniques was emphasized in the proposed seminar.

Cite as

David S. Ebert, Hans Hagen, Kenneth I. Joy, and Daniel A. Keim. 07291 Summary – Scientific Visualization. In Scientific Visualization. Dagstuhl Seminar Proceedings, Volume 7291, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)


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@InProceedings{ebert_et_al:DagSemProc.07291.2,
  author =	{Ebert, David S. and Hagen, Hans and Joy, Kenneth I. and Keim, Daniel A.},
  title =	{{07291 Summary – Scientific Visualization}},
  booktitle =	{Scientific Visualization},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{7291},
  editor =	{David S. Ebert and Hans Hagen and Kenneth I. Joy and Daniel A. Keim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07291.2},
  URN =		{urn:nbn:de:0030-drops-14132},
  doi =		{10.4230/DagSemProc.07291.2},
  annote =	{Keywords: Markov chains, numerical methods, web information retrieval, performance evaluation, intrusion detection, aggregation-disaggregation methods graph-oriented decomposition}
}
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