DaRUS

Metrics

1,167,261 Downloads

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Subject: Computer and Information Science

41 to 50 of 1,553 Results

Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries(Universität Stuttgart) Feb 22, 2024Projects without PN Affiliation The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scal...
Code and benchmark for NPCS, a Native Provenance Computation for SPARQL Feb 21, 2024 - Analytic Computing Asma, Zubaria; Hernández, Daniel; Galárraga, Luis; Flouris, Giorgos; Fundulaki, Irini; Hose, Katja, 2024, "Code and benchmark for NPCS, a Native Provenance Computation for SPARQL", https://doi.org/10.18419/darus-3973, DaRUS, V1 Code for the implementation and benchmark of NPCS, a Native Provenance Computation for SPARQL. The code in this dataset includes the implementation of the NPCS system, which is a middleware for SPARQL endpoints that rewrites queries to queries that annotate answers with provenanc...
Code for From Shapes to Shapes Feb 16, 2024 - Analytic Computing Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/darus-3977, DaRUS, V1 This dataset contains the implementation code for an algorithm to infer SHACL shapes that the graph returned by an SPARQL CONSTRUCT query must satisfy if the input satisfies a given set of SHACL shapes. This dataset also includes an evaluation for the algorithm. The algorithm imp...
Replication data for analyzing stable water isotopologue transport within soils using fractionation parameterizations Feb 16, 2024 - C-X5 Kiemle, Stefanie; Schneider, Jana; Heck, Katharina, 2024, "Replication data for analyzing stable water isotopologue transport within soils using fractionation parameterizations", https://doi.org/10.18419/darus-3572, DaRUS, V1 Replication data to reproduce the results presented in J. Schneider & S. Kiemle, K. Heck, Y. Rothfuss, I. Braud, R. Helmig, J. Vanderborght (2024) Analysis of Experimental and Simulation Data of Evaporation-Driven Isotopic Fractionation in Unsaturated Porous Media. (Under review)...
PDEBench Datasets Feb 13, 2024 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8 This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...
CNVVE Dataset clean audio samples Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "CNVVE Dataset clean audio samples", https://doi.org/10.18419/darus-3898, DaRUS, V1 This CNVVE Dataset contains clean audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective...
Code for Training and Testing CNVVE Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/darus-3896, DaRUS, V1 This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for...
Raw audio samples of the CNVVE dataset Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/darus-3897, DaRUS, V1 This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective fo...
Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material Feb 6, 2024 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization" Rodrigues, Nils; Dennig, Frederik L.; Brandt, Vincent; Keim, Daniel; Weiskopf, Daniel, 2024, "Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material", https://doi.org/10.18419/darus-3451, DaRUS, V1 We evaluated several animations for transitions between scatter plots in a crowd-sourcing study. We published the results in a paper and provide additional information within this supplemental material. Contents: Tables that did not fit into the original paper, due to page limits...
Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations" Feb 6, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences" Aichem, Michael; Klein, Karsten; Kobourov, Stephen; Schreiber, Falk, 2023, "Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations"", https://doi.org/10.18419/darus-3706, DaRUS, V2 This dataset contains the supplemental materials for our publication "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations". The publication reports on an experiment that we conducted to explore the effect...

Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries(Universität Stuttgart)

Feb 22, 2024Projects without PN Affiliation

The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scal...

Code and benchmark for NPCS, a Native Provenance Computation for SPARQL

Feb 21, 2024 - Analytic Computing

Asma, Zubaria; Hernández, Daniel; Galárraga, Luis; Flouris, Giorgos; Fundulaki, Irini; Hose, Katja, 2024, "Code and benchmark for NPCS, a Native Provenance Computation for SPARQL", https://doi.org/10.18419/darus-3973, DaRUS, V1

Code for the implementation and benchmark of NPCS, a Native Provenance Computation for SPARQL. The code in this dataset includes the implementation of the NPCS system, which is a middleware for SPARQL endpoints that rewrites queries to queries that annotate answers with provenanc...

Code for From Shapes to Shapes

Feb 16, 2024 - Analytic Computing

Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/darus-3977, DaRUS, V1

This dataset contains the implementation code for an algorithm to infer SHACL shapes that the graph returned by an SPARQL CONSTRUCT query must satisfy if the input satisfies a given set of SHACL shapes. This dataset also includes an evaluation for the algorithm. The algorithm imp...

Replication data for analyzing stable water isotopologue transport within soils using fractionation parameterizations

Feb 16, 2024 - C-X5

Kiemle, Stefanie; Schneider, Jana; Heck, Katharina, 2024, "Replication data for analyzing stable water isotopologue transport within soils using fractionation parameterizations", https://doi.org/10.18419/darus-3572, DaRUS, V1

Replication data to reproduce the results presented in J. Schneider & S. Kiemle, K. Heck, Y. Rothfuss, I. Braud, R. Helmig, J. Vanderborght (2024) Analysis of Experimental and Simulation Data of Evaporation-Driven Isotopic Fractionation in Unsaturated Porous Media. (Under review)...

PDEBench Datasets

Feb 13, 2024 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8

This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...

CNVVE Dataset clean audio samples

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "CNVVE Dataset clean audio samples", https://doi.org/10.18419/darus-3898, DaRUS, V1

This CNVVE Dataset contains clean audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective...

Code for Training and Testing CNVVE

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/darus-3896, DaRUS, V1

This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for...

Raw audio samples of the CNVVE dataset

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/darus-3897, DaRUS, V1

This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective fo...

Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material

Feb 6, 2024 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization"

Rodrigues, Nils; Dennig, Frederik L.; Brandt, Vincent; Keim, Daniel; Weiskopf, Daniel, 2024, "Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material", https://doi.org/10.18419/darus-3451, DaRUS, V1

We evaluated several animations for transitions between scatter plots in a crowd-sourcing study. We published the results in a paper and provide additional information within this supplemental material. Contents: Tables that did not fit into the original paper, due to page limits...

Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations"

Feb 6, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"

Aichem, Michael; Klein, Karsten; Kobourov, Stephen; Schreiber, Falk, 2023, "Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations"", https://doi.org/10.18419/darus-3706, DaRUS, V2

This dataset contains the supplemental materials for our publication "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations". The publication reports on an experiment that we conducted to explore the effect...

Add Data

Share Dataverse

Link Dataverse

Reset Modifications