cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e189382v2
title: D1-01-Designing an app for alternative access assessments: using interviews to uncover and define user needs

description: To support effective alternative access assessment and service delivery for people with motor impairments, we are developing an app called Access Assistant. This dataset is from the first stage of the project: the interviews we conducted as part of a discovery process to improve our understanding of user needs. We individually interviewed 8 assistive technology practitioners and 3 clients who use alternative access methods, to learn what practitioners were currently doing in their access assessments, identify opportunities for improving current practice, and understand what the assessment process was like for clients. We extracted 236 relevant quotes from interview transcripts, and clustered the quotes using the affinity wall method, yielding 42 themes. We identified the 21 highest priority themes, along with the app requirements that support those themes. Results confirmed the need for a tool to support more effective assessments, with emphasis on taking the worry out of access assessments and supporting early success. Results also revealed specific needs such as flexible workflow, personalized test-drive tasks, and a choice of metrics (including client preference). With a richer understanding of user needs, we are in a much better position to design software that can address those needs.
description: Assistive technology practitioners<br>People with motor impairments who use alternative access methods for electronic devices.
description: Interviews conducted in November and December of 2020, as part of a project within the Rehabilitation Engineering Research Center (RERC) on AAC. The RERC on AAC is a collaborative center committed to advancing knowledge and producing innovative engineering solutions in augmentative and alternative communication (AAC) [https://rerc-aac.psu.edu/]. The purpose of the project is to develop and evaluate an evidence-based protocol and software app to support effective alternative access assessment and service delivery for individuals with severe motor impairments. The dataset is in one file, which includes: 1.The interview purpose and questions 2. Table with basic characteristics of the participants 3. Transcripts for each participant.
DOI: 10.3886/e189382
title: D1-01-Designing an app for alternative access assessments: using interviews to uncover and define user needs

description: To support effective alternative access assessment and service delivery for people with motor impairments, we are developing an app called Access Assistant. This dataset is from the first stage of the project: the interviews we conducted as part of a discovery process to improve our understanding of user needs. We individually interviewed 8 assistive technology practitioners and 3 clients who use alternative access methods, to learn what practitioners were currently doing in their access assessments, identify opportunities for improving current practice, and understand what the assessment process was like for clients. We extracted 236 relevant quotes from interview transcripts, and clustered the quotes using the affinity wall method, yielding 42 themes. We identified the 21 highest priority themes, along with the app requirements that support those themes. Results confirmed the need for a tool to support more effective assessments, with emphasis on taking the worry out of access assessments and supporting early success. Results also revealed specific needs such as flexible workflow, personalized test-drive tasks, and a choice of metrics (including client preference). With a richer understanding of user needs, we are in a much better position to design software that can address those needs.
description: Assistive technology practitioners<br>People with motor impairments who use alternative access methods for electronic devices.
description: Interviews conducted in November and December of 2020, as part of a project within the Rehabilitation Engineering Research Center (RERC) on AAC. The RERC on AAC is a collaborative center committed to advancing knowledge and producing innovative engineering solutions in augmentative and alternative communication (AAC) [https://rerc-aac.psu.edu/]. The purpose of the project is to develop and evaluate an evidence-based protocol and software app to support effective alternative access assessment and service delivery for individuals with severe motor impairments. The dataset is in one file, which includes: 1.The interview purpose and questions 2. Table with basic characteristics of the participants 3. Transcripts for each participant.
DOI: 10.3886/e189382v1
title: D1-01-Designing an app for alternative access assessments: using interviews to uncover and define user needs

description: To support effective alternative access assessment and service delivery for people with motor impairments, we are developing an app called Access Assistant. This dataset is from the first stage of the project: the interviews we conducted as part of a discovery process to improve our understanding of user needs. We individually interviewed 8 assistive technology practitioners and 3 clients who use alternative access methods, to learn what practitioners were currently doing in their access assessments, identify opportunities for improving current practice, and understand what the assessment process was like for clients. We extracted 236 relevant quotes from interview transcripts, and clustered the quotes using the affinity wall method, yielding 42 themes. We identified the 21 highest priority themes, along with the app requirements that support those themes. Results confirmed the need for a tool to support more effective assessments, with emphasis on taking the worry out of access assessments and supporting early success. Results also revealed specific needs such as flexible workflow, personalized test-drive tasks, and a choice of metrics (including client preference). With a richer understanding of user needs, we are in a much better position to design software that can address those needs.
description: Assistive technology practitioners<br>People with motor impairments who use alternative access methods for electronic devices.
description: Interviews conducted in November and December of 2020, as part of a project within the Rehabilitation Engineering Research Center (RERC) on AAC. The RERC on AAC is a collaborative center committed to advancing knowledge and producing innovative engineering solutions in augmentative and alternative communication (AAC) [https://rerc-aac.psu.edu/]. The purpose of the project is to develop and evaluate an evidence-based protocol and software app to support effective alternative access assessment and service delivery for individuals with severe motor impairments. The dataset is in one file, which includes: 1.The interview purpose and questions 2. Table with basic characteristics of the participants 3. Transcripts for each participant.
DOI: 10.3886/e189382v3
title: D1-01-Designing an app for alternative access assessments: using interviews to uncover and define user needs

description: To support effective alternative access assessment and service delivery for people with motor impairments, we are developing an app called Access Assistant. This dataset is from the first stage of the project: the interviews we conducted as part of a discovery process to improve our understanding of user needs. We individually interviewed 8 assistive technology practitioners and 3 clients who use alternative access methods, to learn what practitioners were currently doing in their access assessments, identify opportunities for improving current practice, and understand what the assessment process was like for clients. We extracted 236 relevant quotes from interview transcripts, and clustered the quotes using the affinity wall method, yielding 42 themes. We identified the 21 highest priority themes, along with the app requirements that support those themes. Results confirmed the need for a tool to support more effective assessments, with emphasis on taking the worry out of access assessments and supporting early success. Results also revealed specific needs such as flexible workflow, personalized test-drive tasks, and a choice of metrics (including client preference). With a richer understanding of user needs, we are in a much better position to design software that can address those needs.
description: Assistive technology practitioners<br>People with motor impairments who use alternative access methods for electronic devices.
description: Interviews conducted in November and December of 2020, as part of a project within the Rehabilitation Engineering Research Center (RERC) on AAC. The RERC on AAC is a collaborative center committed to advancing knowledge and producing innovative engineering solutions in augmentative and alternative communication (AAC) [https://rerc-aac.psu.edu/]. The purpose of the project is to develop and evaluate an evidence-based protocol and software app to support effective alternative access assessment and service delivery for individuals with severe motor impairments. The dataset is in one file, which includes: 1.The interview purpose and questions 2. Table with basic characteristics of the participants 3. Transcripts for each participant.
DOI: 10.5517/ccdc.csd.cc2cpzdg
title: CCDC 2195866: Experimental Crystal Structure Determination

description: Related Article: Vivek W. Bhoyare, E. Daiann Sosa Carrizo, Chetan C. Chintawar, Vincent Gandon, Nitin T. Patil|2023|J.Am.Chem.Soc.|145|8810|doi:10.1021/jacs.3c02544
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cpzkm
title: CCDC 2195871: Experimental Crystal Structure Determination

description: Related Article: Vivek W. Bhoyare, E. Daiann Sosa Carrizo, Chetan C. Chintawar, Vincent Gandon, Nitin T. Patil|2023|J.Am.Chem.Soc.|145|8810|doi:10.1021/jacs.3c02544
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cpzrt
title: CCDC 2195877: Experimental Crystal Structure Determination

description: Related Article: Vivek W. Bhoyare, E. Daiann Sosa Carrizo, Chetan C. Chintawar, Vincent Gandon, Nitin T. Patil|2023|J.Am.Chem.Soc.|145|8810|doi:10.1021/jacs.3c02544
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzlff
title: CCDC 2233935: Experimental Crystal Structure Determination

description: Related Article: Wilhelm Klein|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzptx
title: CCDC 2234040: Experimental Crystal Structure Determination

description: Related Article: Liming Zhang, Haoran Xu, Weitao Liu, Chengwen Li, Yilin Zhao, Linhai Yan, Yangping Liu, Xianchao Cheng, Xiao-Song Xue, Guifang Han|2023|Org.Lett.|25|2889|doi:10.1021/acs.orglett.3c00860
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.2599196
title: TAU Spatial Sound Events 2019 - Ambisonic and Microphone Array, Development Datasets

description: This package consists of two development datasets, <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> and <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong>. These datasets contain recordings from an identical scene, with <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> providing four-channel First-Order Ambisonic (FOA) recordings while <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> provides four-channel directional microphone recordings from a tetrahedral array configuration. Both formats are extracted from the same microphone array. The recordings in the two datasets consist of stationary point sources from multiple sound classes each associated with a temporal onset and offset time, and DOA coordinate represented using azimuth and elevation angle. These development datasets are part of the DCASE 2019 Sound Event Localization and Detection Task.

Both the development set consists of 400, one minute long recordings sampled at 48000 Hz, and divided into four cross-validation splits of 100 recordings each. These recordings were synthesized using spatial room impulse response (IRs) collected from five indoor locations, at 504 unique combinations of azimuth-elevation-distance. Furthermore, in order to synthesize the recordings, the collected IRs were convolved with isolated sound events dataset from DCASE 2016 task 2. Finally, to create a realistic sound scene recording, natural ambient noise collected in the IR recording locations was added to the synthesized recordings such that the average SNR of the sound events was 30 dB.

The IRs were collected in Finland by Tampere University between 12/2017 - 06/2018. The data collection received funding from the European Research Council, grant agreement 637422 EVERYSOUND.

<strong>Download instructions</strong>

The three files,  <strong><em>foa_dev.z01</em></strong>,<strong><em> foa_dev.z02</em></strong> and <strong><em>foa_dev.zip</em></strong>, correspond to audio data of <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> development dataset.<br>
The two files, <strong><em>mic_dev.z01</em></strong> and, <strong><em>mic_dev.zip</em></strong>, correspond to audio data of <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> development dataset.<br>
The <strong><em>metadata_dev.zip</em></strong> is the common metadata for both <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> and <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> development datasets.

Download the zip files corresponding to the dataset of interest and use your favorite compression tool to unzip these split zip files.<br>
DOI: 10.5281/zenodo.3377088
title: TAU Spatial Sound Events 2019 - Ambisonic and Microphone Array, Evaluation Datasets

description: This package consists of two evaluation datasets, <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> and <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong>. These datasets contain recordings from an identical scene, with <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> providing four-channel First-Order Ambisonic (FOA) recordings while <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> provides four-channel directional microphone recordings from a tetrahedral array configuration. Both formats are extracted from the same microphone array. The recordings in the two datasets consist of stationary point sources from multiple sound classes each associated with a temporal onset and offset time, and DOA coordinate represented using azimuth and elevation angle. These evaluation datasets are part of the DCASE 2019 Sound Event Localization and Detection Task. The corresponding development datasets can be downloaded here. The IRs were collected in Finland by Tampere University between 12/2017 - 06/2018. The data collection received funding from the European Research Council, grant agreement 637422 EVERYSOUND. The <strong>foa_eval.zip</strong>, correspond to audio data of <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> evaluation dataset. The <strong>mic_eval.zip</strong>, correspond to audio data of <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> evaluation dataset. -- Version 2 updates -- The DCASE 2019 sound event localization and detection task has now ended. Hence we are releasing the reference labels for the evaluation dataset in this version. The <strong><em>metadata_eval.zip</em></strong> is the common metadata for both <strong>TAU Spatial Sound Events 2019 - Ambisonic</strong> and <strong>TAU Spatial Sound Events 2019 - Microphone Array</strong> evaluation datasets. The <strong>short2longnames.txt</strong> file consists of the corresponding names for each recording in the dataset in the development-set format, i.e., including the information of the impulse response location and the maximum number of overlapping sound events in the recording. Download the zip files corresponding to the dataset of interest and use your favorite compression tool to unzip these split zip files.<br>
DOI: 10.25345/c5tm72b1m
title: MassIVE MSV000091831 - Proteomics of SEC and IEX fractionated Mouse Embryonic Stem Cells
title: Mouse embryonic stem cells were lysed in Pierce IP Lysis buffer and 2 mg of the clarified extract was fractionated on an HPLC SEC column and 2 mg was fractionated on an HPLC IEX mixed bed column. All fractions were reduced, alkylated, and trypsin digested for mass spectrometry as in Mallam et al. 2019 (PMID: 31665645). Data were collected on an Orbitrap Fusion mass spectrometer using a data dependent 75 minute topspeed method. Dissociation for SEC fractions was by CID, and for IEX fractions was by HCD. RAW files were converted to mzXML and searched using an MSBlender analysis pipeline.
DOI: 10.3886/e127803v1-137721
title: Data and Code for The Effects of the 1930s HOLC “Redlining” Maps

description: This study uses a boundary design and propensity score methods to study the effects of the 1930s-era HOLC “redlining” maps on the long-run trajectories of urban neighborhoods. The maps led to reduced homeownership rates, house values, and rents and increased racial segregation in later decades. A comparison on either side of a city-level population cutoff that determined whether maps were drawn finds broadly similar conclusions. These results suggest the HOLC maps had meaningful and lasting effects on the development of urban neighborhoods through reduced credit access and subsequent disinvestment.
DOI: 10.5281/zenodo.7884397
title: Electron Diffraction (MicroED) Datasets for Ipragliflozin (Glacios TEM with a CETA-D)

description: Electron diffraction datasets collected from a chiral pharmaceutical compound. Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services) Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode) Collection Software: Leginon (Cheng, et. al. 2021)* Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded) Grid: Ted Pella 01840 Sample: C<sub>21</sub>H<sub>21</sub>FO<sub>5</sub>S, (1<em>S</em>)-1,5-anhydro-1-<em>C</em>-{3-[(1-benzothiophen-2-yl)methyl]-4-fluorophenyl}-D-glucitol, 404.45 g/mol Structure: CCDC 2260059 * Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value. A data processing tutorial is available for processing data collected with this setup using DIALS: https://dials.github.io/documentation/tutorials/3DED/Biotin.html
DOI: 10.5281/zenodo.7884398
title: Electron Diffraction (MicroED) Datasets for Ipragliflozin (Glacios TEM with a CETA-D)

description: Electron diffraction datasets collected from a chiral pharmaceutical compound. Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services) Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode) Collection Software: Leginon (Cheng, et. al. 2021)* Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded) Grid: Ted Pella 01840 Sample: C<sub>21</sub>H<sub>21</sub>FO<sub>5</sub>S, (1<em>S</em>)-1,5-anhydro-1-<em>C</em>-{3-[(1-benzothiophen-2-yl)methyl]-4-fluorophenyl}-D-glucitol, 404.45 g/mol Structure: CCDC 2260059 * Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value. A data processing tutorial is available for processing data collected with this setup using DIALS: https://dials.github.io/documentation/tutorials/3DED/Biotin.html
DOI: 10.5517/ccdc.csd.cc2cqct9
title: CCDC 2196251: Experimental Crystal Structure Determination

description: Related Article: Zhen Han, Yubing Si, Xi-Yan Dong, Jia-Hua Hu, Chong Zhang, Xuan-Hui Zhao, Jia-Wang Yuan, Yan Wang, Shuang-Quan Zang|2023|J.Am.Chem.Soc.|145|6166|doi:10.1021/jacs.2c12055
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cqcvb
title: CCDC 2196252: Experimental Crystal Structure Determination

description: Related Article: Zhen Han, Yubing Si, Xi-Yan Dong, Jia-Hua Hu, Chong Zhang, Xuan-Hui Zhao, Jia-Wang Yuan, Yan Wang, Shuang-Quan Zang|2023|J.Am.Chem.Soc.|145|6166|doi:10.1021/jacs.2c12055
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cqcwc
title: CCDC 2196253: Experimental Crystal Structure Determination

description: Related Article: Zhen Han, Yubing Si, Xi-Yan Dong, Jia-Hua Hu, Chong Zhang, Xuan-Hui Zhao, Jia-Wang Yuan, Yan Wang, Shuang-Quan Zang|2023|J.Am.Chem.Soc.|145|6166|doi:10.1021/jacs.2c12055
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.