cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f75q4t9w
title: Continuous Monitoring and Synoptic Mapping of Nearshore Water Quality, Currents, and Bathymetry in Lake Michigan at 63rd Street Beach at Hyde Park, Illinois

description: These data were collected as part of the Great Lakes Restoration Initiative (GLRI) project template 678-1 entitled Evaluate immediate and long-term BMP effectiveness of GLRI restoration efforts at urban beaches on Southern and Western Lake Michigan. This project is evaluating the effectiveness of projects that are closely associated with restoration of local habitat and contact recreational activities at two GLRI funded sites in Southern Lake Michigan and one non-GLRI site in Western Lake Michigan. Evaluation of GLRI projects will assess whether goals of recipients are on track and identify any developing unforeseen consequences. Including a third, non-GLRI project site in the evaluation allows comparison between restoration efforts in GLRI and non-GLRI funded projects. Projections and potential complications associated with climate change impacts on restoration resiliency are also being assessed. Two of the three sites to receive evaluation represent some of the most highly contaminated beaches in the United States and include restoration BMPs which could benefit urban beaches and nearshore areas throughout the Great Lakes. The urban beaches chosen for evaluation are at various stages of the restoration process and located in Indiana (Jeorse Park Beach), Illinois (63rd Street Beach), and Wisconsin (North Beach). Evaluation of effectiveness of restoration efforts and resiliency to climate change at urban beaches will provide vital information on the success of restoration efforts and identify potential pitfalls that will help maximize success of future GLRI beach and nearshore restoration projects. Data used for evaluation include continuous monitoring and synoptic mapping of nearshore currents, bathymetry, and water quality to examine nearshore transport under a variety of conditions. In addition, biological evaluations rely upon daily indicator bacteria monitoring, microbial community and shorebird surveys, recreational usage, and other ancillary water quality data.
DOI: 10.5066/f7pn93v7
title: Continuous Monitoring and Synoptic Mapping of Nearshore Water Quality, Currents, and Bathymetry in Lake Michigan at Jeorse Park Beach near Gary, Indiana

description: These data were collected as part of the Great Lakes Restoration Initiative (GLRI) project template 678-1 entitled 'Evaluate immediate and long-term BMP effectiveness of GLRI restoration efforts at urban beaches on Southern and Western Lake Michigan'. This project is evaluating the effectiveness of projects that are closely associated with restoration of local habitat and contact recreational activities at two GLRI funded sites in Southern Lake Michigan and one non-GLRI site in Western Lake Michigan. Evaluation of GLRI projects will assess whether goals of recipients are on track and identify any developing unforeseen consequences. Including a third, non-GLRI project site in the evaluation allows comparison between restoration efforts in GLRI and non-GLRI funded projects. Projections and potential complications associated with climate change impacts on restoration resiliency are also being assessed. Two of the three sites to receive evaluation represent some of the most highly contaminated beaches in the United States and include restoration BMPs which could benefit urban beaches and nearshore areas throughout the Great Lakes. The urban beaches chosen for evaluation are at various stages of the restoration process and located in Indiana (Jeorse Park Beach), Illinois (63rd Street Beach), and Wisconsin (North Beach). Evaluation of effectiveness of restoration efforts and resiliency to climate change at urban beaches will provide vital information on the success of restoration efforts and identify potential pitfalls that will help maximize success of future GLRI beach and nearshore restoration projects. Data used for evaluation include continuous monitoring and synoptic mapping of nearshore currents, bathymetry, and water quality to examine nearshore transport under a variety of conditions. In addition, biological evaluations rely upon daily indicator bacteria monitoring, microbial community and shorebird surveys, recreational usage, and other ancillary water quality data.
DOI: 10.5066/f7445k05
title: Vertical Land Change in Select Counties of Kentucky, Minnesota, and Wisconsin

description: The Vertical Land Change project is an assessment of the impacts of surface mining in Perry County, Kentucky, the Mesabi Iron Range in northeastern Minnesota, and the west central part of Wisconsin. This project builds and expands upon previous vertical land change efforts (Gesch, 2006) by conducting research into the issues surrounding the integration of 3D data products with 2D remote sensing imagery products to improve monitoring, assessment, and projection of land change by including additional vertical and volumetric information. These efforts are combined to support multi-temporal 3D land change research. The objective of this research is to understand the use of multi-temporal, multi-resolution 3D geospatial data for land change monitoring and assessment, acquired with a number of different sensors, including lidar, IFSAR, and stereo imagery, on a variety of platforms, including ground-based, airborne, and spaceborne. References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf. USGS Topographic Change Web site located at https://topochange.cr.usgs.gov/.
DOI: 10.5066/f7513wpc
title: Barrier island habitat map and vegetation survey, Dauphin Island, AL, 2015

description: This dataset includes barrier island land cover types collected from mid-November 2015 to mid-December 2015 along randomly placed transects at seven sites throughout the east end of Dauphin Island. Specifically, this data collection included characterizing land cover types and measuring horizontal position and elevation. We characterized plant community composition and structure for a subset of these points (see Vegetation Survey Data Table). This work was conducted through a joint effort by the State of Alabama, the U.S. Geological Survey, and the U.S. Army Corps of Engineers to evaluate the feasibility of various restoration alternatives and how specific alternatives might increase the resiliency and sustainability of Dauphin Island. The overarching goal of the aforementioned effort is to preserve and enhance the ecological functions and values of the island. This product provides a powerful tool for tracking changes to barrier island habitats over time. This data release includes the following three components, which are included in the attached ZIP file: 1) Dauphin Island Habitat Map (Raster data) 2) Land Cover and Vegetation Field Data Points (Vector data) 3) Vegetation Survey Data (Tabular data)
DOI: 10.5066/f7jq0z63
title: Bd and Bsal prevalence in Gulf Coast waterdogs captured from St. Tammany Parish, Louisiana, in 2015

description: The dataset includes information on all 76 Gulf Coast Waterdogs captured including sex and size information along with the results of the tests for the two fungal pathogens.
DOI: 10.5281/zenodo.816258
title: Character coding comparisons: matrices of 115 traits for hominoids in TNT format.

description: TNT_character_matrix_positions.csv: provides descriptions of the 115 characters and their positions in the character matrices. TNT_95CI_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is a 95% confidence interval for the species mean. TNT_DVC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using divergence coding. TNT_GWC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using generalized gap weighting. TNT_HSC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using homogeneous subset coding. TNT_IDO_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using identification of overlap coding. TNT_Mean_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is a species mean.
DOI: 10.5281/zenodo.816259
title: Character coding comparisons: matrices of 115 traits for hominoids in TNT format.

description: TNT_character_matrix_positions.csv: provides descriptions of the 115 characters and their positions in the character matrices. TNT_95CI_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is a 95% confidence interval for the species mean. TNT_DVC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using divergence coding. TNT_GWC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using generalized gap weighting. TNT_HSC_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using homogeneous subset coding. TNT_IDO_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is coded using identification of overlap coding. TNT_Mean_character_matrix.tnt: TNT format character matrix with 115 traits. Each trait value is a species mean.
DOI: 10.14469/hpc/2686
title: ene 14-R conf 1 G=-1613.143623

description: Gaussian Calculation
DOI: 10.14469/hpc/2687
title: ene VCD 14-S conf 1 H-bond G=-1613.142524

description: Gaussian Calculation
DOI: 10.14469/hpc/2688
title: ene VCD 14-S conf 2 H-bond atrop G=-1613.140345

description: Gaussian Calculation
DOI: 10.14469/hpc/2689
title: diol 14-S conf 2 H-bond atrop G=-1764.752782

description: Gaussian Calculation
DOI: 10.14469/hpc/2690
title: Methanol in methanol, mpw1pw91/aug-cc-pvdz

description: Gaussian Calculation
DOI: 10.4119/unibi/2696589
title: Using a cVEP-based Brain-Computer Interface to control a virtual agent -- dataset
DOI: 10.14469/hpc/2691
title: diol mPW1PW91/aug-cc-pvdz NMR 14-S H=-1765.28844087 G=-1764.755455

description: Gaussian Calculation
DOI: 10.14469/hpc/2692
title: diol 14-R conf 3 H-bond atrop G=-1764.756327

description: Gaussian Calculation
DOI: 10.14469/hpc/2693
title: diol 14-R conf 2 H-bond G=-1764.745771

description: Gaussian Calculation
DOI: 10.14469/hpc/2694
title: diol 14-R conf 1 G=-1764.750955

description: Gaussian Calculation
DOI: 10.14469/hpc/2695
title: diol 14-R G=-1764.750959

description: Gaussian Calculation
DOI: 10.14469/hpc/2696
title: Diol 14-S conf 1 + H-bond H=-1765.28849240 G=-1764.754988

description: Gaussian Calculation
DOI: 10.4119/unibi/2699375
title: Supplementary Material for "Multi-Channel Sonification of Human EEG"

description: The electroencephalogram (EEG) provides a diagnostically important stream of multivariate data of the activity of the human brain. Various sonification strategies have been proposed but auditory space has rarely been used to give cues about the location of specific events. Here we introduce a multivariate event-based sonification that, in addition to displaying salient rhythms, uses pitch and spatial location to provide such cues. Using clinical recording with epileptic seizures we demonstrate how the spatio-temporal characteristics of EEG can be perceived in such an approach.
DOI: 10.4119/unibi/2699954
title: Supplementary Material for "Sonified Epilectic Rhythms"

description: We describe techniques to sonify rhythmic activity of epileptic seizures as measured by human EEG. Event-based mapping of parameters is found to be informative in terms of auto- and cross-correlations of the multivariate data. For the study, a group of patients with childhood absence seizures are selected. We find consistent intra-patient conservation of the rhythmic pattern as well as inter-patient variations, especially in terms of cross-correlations. The sound synthesis is suitable for online sonification. Thus, the application of the proposed sonification in clinical monitoring is possible.
DOI: 10.4119/unibi/2700564
title: Supplementary Material for "A Malleable Device with Applications to Sonification-based Data Exploration"

description: This article introduces a novel human computer interaction device, developed in the scope of a Master’s Thesis [1]. The device allows continuous localized interaction by providing a malleable interaction surface. Diverse multi-finger as well as multi-handed manipulations can be applied. Furthermore, the device acts as a tangible user interface object, integrated into a tangible computing framework called tDesk [2]. Software to convert the malleable element’s shape into an internal surface representation has been developed. Malleable interactions are applied to a new Model-based Sonification approach for exploratory data analysis. High-dimensional data are acoustically explored via their informative interaction sound in result to excitation.
DOI: 10.4119/unibi/2700876
title: Supplementary Material for "Sonification of Group Behavior for Analysis and Training of Sports Tactics"

description: Sound Example: Sonification for a 6:0-defense in handball The sonifications are computed in real-time mode with csound. visualization and sonification are synchronized, an example defense situation is shown in the following screenshot. Each defense player is represented in the current design by an own percussive instrument. <br> Here are the sound samples for the defense players, from the left to the right: * [AL (6) outer left (wav, 50k)](https://pub.uni-bielefeld.de/download/2700876/2700882) * [HL (5) half left (wav, 30k)](https://pub.uni-bielefeld.de/download/2700876/2700880) * [ML (4) middle left (wav, 50k)](https://pub.uni-bielefeld.de/download/2700876/2700877) * [MR (3) middle right(wav, 50k)](https://pub.uni-bielefeld.de/download/2700876/2700878) * [HR (2) half right (wav, 15k)](https://pub.uni-bielefeld.de/download/2700876/2700879) * [AR (1) outer right (wav, 30k)](https://pub.uni-bielefeld.de/download/2700876/2700881) The two videos show a defense with some errors (particularly of MR). The deviation from the nominal behavior gets well audible. * Sonification example 1 - without relevance mapping <br> [Movie1 (avi, 6Mb)](https://pub.uni-bielefeld.de/download/2700876/2700883) * Sonification example 1 - with relevance mapping <br> [Movie2 (avi, 4Mb)](https://pub.uni-bielefeld.de/download/2700876/2700884) <br>
DOI: 10.4119/unibi/2700941
title: Supplementary Material for "The Local Heat Exploration Model for Interactive Sonification"

description: This paper presents a new sonification model for the exploration of topographically ordered high-dimensional data (multi-parameter maps, volume data) where each data item consists of a position and feature vector. The sonification model implements a common metaphor from thermodynamics that heat can be interpreted as stochastic motion of 'molecules'. The latter are determined by the data under examination, and 'live' only in the feature space. Heat-induced interactions cause acoustic events that fuse to a granular sound texture which conveys meaningful information about the underlying distribution in feature space. As a second ingredient of the model, data selection is achieved by a separated navigation process in position space using a dynamic aura model, such that heat can be induced locally. Both, a visual and an auditory display are driven by the underlying model. We exemplify the sonification by means of interaction examples for different high-dimensional distributions. ## Examples In the paper the following sounds are described and discussed: ### Controlled Center <br> Aura Position in Controlled Center Example #### Gaussian data sets <br> Spectrogram of Gauss Example with lambda = 3 <br> [lambda = 3 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700943) <br> Spectrogram of Gauss Example with lambda = 30 <br> [lambda = 30 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700942) <br> Spectrogram of Gauss Example with lambda = 300 <br> [lambda = 300 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700945) #### Hollow Sphere data sets <br> Spectrogram of Sphere Example with lambda = 5 <br> [lambda = 5 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700948) <br> Spectrogram of Sphere Example with lambda = 50 <br> [lambda = 50 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700947) <br> Spectrogram of Sphere Example with lambda = 100 <br> [lambda = 100 (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2700946) ### Interactive <br> Aura Center in Interactive Example <br> <br> Spectrogram of Interactive Example <br> [Hear it (mp3, 1.3MB)](https://pub.uni-bielefeld.de/download/2700941/2704527)
DOI: 10.4119/unibi/2700951
title: Supplementary Material for "Polyrhythmic Organization of Coupled Nonlinear Oscillators"

description: We study the rhythmic organization of coupled nonlinear oscillators. If oscillators with non-identical internal frequency are coupled, they generate a great variety of periodic and chaotic rhythmic patterns. Sonification of these patterns suggests their characterization in terms of polyrhythms: each oscillatory unit subdivides "measures" of equal or varying length differently. For the case of two coupled oscillators, the organization of these polyrhythms is exemplified as a function of the internal frequency ratio and the coupling strength. Some sonification strategies are presented which aid to detect complex rhythmic relationships between oscillators. The results may be of importance for the analysis of complex multivariate time series like human EEG. * A 4:3 Polyrhythm with parameters as in Fig. 2 * S1 (mp3, 306k) epsilon=0.75, D=0.005 * A chaotic polyrhythm with parameters as in Fig. 3 in two different speeds * S2a (mp3,494k) epsilon=0.74, D=0.005 * S2b (mp3, 1.2M) epsilon=0.74, D=0.005, T=50sec * An intermittent polyrhythm with parameters I=0.0605, epsilon=0.6445, D=0.005 * S3 (mp3, 329k) T = 20sec * A polyrhythm in a 3 oscillator system with internal frequencies set to 5:4:3 and D=0.01 * S4 (mp3, 1.4M) * A chaotic polyrhythm in a three oscillator system with internal frequencies set to 1.0:0.9:0.55 and D=0.0032 (other parameters as in eq. 1). * S5a (mp3, 5sec, 95k) * S5b (mp3, 15sec, 250k) * S5c (mp3, 45sec, 720k) * Sequence of rhythms as parameter epsilon is continuously varied from 0.5 to 0.99 * S6 (mp3, 494k) * Sequence of rhythms as in S5 but with total duration 60 sec * S7 (mp3, 1.4M)
DOI: 10.4119/unibi/2700964
title: Supplementary Material for "Using Sonification to detect weak cross-correlations in coupled excitable systems"

description: We study cross-correlations in irregularly spiking systems. A single system displays spiking sequences that resemble a stochastic (Poisson) process. Linear coupling between two systems leaves the inter-spike interval distribution qualitatively unchanged but induces cross-correlations between the units. For strong coupling this leads to synchronization as expected but for weak coupling, both a good statistic and sonification reveal the presence of ``motifs'', preferred short firing sequences which are due to the deterministic spiking mechanism. We argue that the use of sonification for time series analysis is superior in the case where intrinsic non-stationarity of an experiment cannot be ruled out. #### Audifications S1a: compression factor 2 S1b: compression factor 6 S1c: compression factor 50 #### Amplitude Modulation S2a: rate 0.1 S2b: rate 0.2 S2c: rate 1 #### Event-based rhythms S3a: r=1 D=0 S3b: r=1 D=0.00125 S3c: r=5 D=0 S3d: r=5 D=0.00125 #### Timbre mapping S4a: 20sec D=0 S4d: 20sec D=0.00125 S4b: 60sec D=0 S4e: 60sec D=0.00125 S4c: 240sec D=0 S4f: 240sec D=0.00125 #### Sonifications for coupling drift S5a: D=0..0.005,20sec rhythm S5b: D=0..0.005,20sec pitch deviation S5c: D=0..0.005,20sec timbre #### Timbre Sonifications of Coupling drift S6a: 20sec, D=0..0.00125 S6b: 30sec, D=0..0.00125 S6c 20sec, D=0..0.005 S6d 30sec, D=0..0.005
DOI: 10.4119/unibi/2700990
title: Supplementary Material for "The Sonification of Rhythms in Human Electroencephalogram"

description: We use sonification of temporal information extracted from scalp EEG to characterize the dynamic properties of rhythms in certain frequency bands. Sonification proves particularly useful in the simultaneous monitoring of several EEG channels. Our results suggest sonification as an important tool in the analysis of multivariate data with subtle correlation differences.
DOI: 10.4119/unibi/2700998
title: Supplementary Material for "Gesture Desk -- An Integrated Multi-Modal Interface for Interactive Sonification"

description: This paper presents the gesture desk, a new platform for a human-computer interface at a regular computer workplace. It extends classical input devices like keyboard and mouse by arm and hand gestures, without the need to use any inconvenient accessories like data gloves or markers. A central element is a "gesture box" containing two infrared cameras and a color camera which is positioned under a glass desk. Arm and hand motions are tracked in three dimensions. A synchronizer board has been developed to provide an active glare-free IR-illumination for robust body and hand tracking. As a first application, we demonstrate interactive real-time browsing and querying of auditory self-organizing maps (AuSOMs). An AuSOM is a combined visual and auditory presentation of high-dimensional data sets. Moving the hand above the desk surface allows to select neurons on the map and to manipulate how they contribute to data sonification. Each neuron is associated with a prototype vector in high-dimensional space, so that a set of 2D-topologically ordered feature maps is queried simultaneously. The level of detail is selected by hand altitude over the table surface, allowing to emphasize or deemphasize neurons on the map.
DOI: 10.4119/unibi/2701097
title: Supplementary Material for "Principal Curve Sonification"

description: This paper describes a new approach to render sonifications for high-dimensional data, allowing the user to perceive the main structure of the data distribution. This is achieved by computing the principal curve of the data set, which is a trajectory that passes through the middle of the data and allows to define a time order on the data points. The sonification can be imagined as the time-variant auditory scene, perceived while moving along the principal curve. In this paper a method for computing principal curves is presented, the sonification concept is introduced and some sonification examples are given.
DOI: 10.4119/unibi/2701116
title: Supplementary Material for "Listen to your Data: Model-Based-Sonification for Data-Analysis"

description: Sonification is the use of non-speech audio to convey information. We are developing tools for interactive data exploration, which make use of sonification for data presentation. In this paper, model-based sonification is presented as a concept to design auditory displays. Two designs are described: (1) particle trajectories in a data potential is a sonification model to reveal information about the clustering of vectorial data and (2)data-sonograms is a sonification for data from a classification problem to reveal information about the mixing of distinct classes. Sound Examples 2+3 with Model II Data-Sonograms: These examples present Data-Sonograms of the iris data set. Iris_nm is a sonogram where the shock wave starts at the mean of all instances of class n. The local entropy S is computed using instances of class n and m. Thus the class border between class n and m is sonified.