cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16917616
title: Course-based research to advance undergraduate education, science and management

description: <i>prepared by Mathis L. Messager (messamat@uw.edu), November 2021</i><br>This documentation describes the survey data collected for the research article: Messager, M. L., Comte, L., Couto, T. B. A., Koontz, E. D., Kuehne, L. M., Rogosch, J. S., Stiling, R. R., Olden, J.D. (In press). Course-based research to advance undergraduate education, science and management. <i>Frontiers in Ecology and the Environment.</i><br><b>Abstract</b>Every year, field excursions engage students of ecology in experiential learning that results in wide-ranging and well-documented pedagogical benefits. Much less appreciated, however, is the potential for these excursions to contribute long-term data that advance scientific knowledge and natural resource management. Here we explore this potential by first providing a global synthesis of field data collection, mapping the geography, temporal extent and type of data collected by students worldwide, and calling attention to the associated benefits and challenges for course instructors. We then offer perspectives on how undergraduate courses in ecology can more broadly contribute to science, management, and policy. Finally, we highlight how existing frameworks, resources and networks, enhanced institutional support, and synergies with the broader science community can help undergraduate ecology courses achieve their full potential for contributing to both education and science for society.<br><b>Repository content</b>1.Messageretal2021_FEE_surveyresults_filtered_formatted.csv: a comma-separated value (CSV) text file containing unedited yet filtered survey responses from instructors who currently teach or have taught a class involved field ecological data collection. 2. Messageretal2021_FEE_surveyquestions.pdf: a copy of the survey as seen by the respondents. <br><b>Usage notes:</b><b>- </b>Any identifying information was removed, including site location or semi-structured and unstructured responses.- Column names like Q2.1 correspond to unique identifiers found at the beginning of each question in the PDF. For multiple questions, each possible response is assigned to a different column and all non-selected responses have a value of -99.- Across questions, -99 is the equivalent of NA.- Note that there was a dysfunction in the survey instrument which made Q10.2, Q16.7 invisible to respondents.<br><br>Please reach out to messamat@uw.edu for any question.
DOI: 10.6084/m9.figshare.16917616.v1
title: Course-based research to advance undergraduate education, science and management

description: <i>prepared by Mathis L. Messager (messamat@uw.edu), November 2021</i><br>This documentation describes the survey data collected for the research article: Messager, M. L., Comte, L., Couto, T. B. A., Koontz, E. D., Kuehne, L. M., Rogosch, J. S., Stiling, R. R., Olden, J.D. (In press). Course-based research to advance undergraduate education, science and management. <i>Frontiers in Ecology and the Environment.</i><br><b>Abstract</b>Every year, field excursions engage students of ecology in experiential learning that results in wide-ranging and well-documented pedagogical benefits. Much less appreciated, however, is the potential for these excursions to contribute long-term data that advance scientific knowledge and natural resource management. Here we explore this potential by first providing a global synthesis of field data collection, mapping the geography, temporal extent and type of data collected by students worldwide, and calling attention to the associated benefits and challenges for course instructors. We then offer perspectives on how undergraduate courses in ecology can more broadly contribute to science, management, and policy. Finally, we highlight how existing frameworks, resources and networks, enhanced institutional support, and synergies with the broader science community can help undergraduate ecology courses achieve their full potential for contributing to both education and science for society.<br><b>Repository content</b>1.Messageretal2021_FEE_surveyresults_filtered_formatted.csv: a comma-separated value (CSV) text file containing unedited yet filtered survey responses from instructors who currently teach or have taught a class involved field ecological data collection. 2. Messageretal2021_FEE_surveyquestions.pdf: a copy of the survey as seen by the respondents. <br><b>Usage notes:</b><b>- </b>Any identifying information was removed, including site location or semi-structured and unstructured responses.- Column names like Q2.1 correspond to unique identifiers found at the beginning of each question in the PDF. For multiple questions, each possible response is assigned to a different column and all non-selected responses have a value of -99.- Across questions, -99 is the equivalent of NA.- Note that there was a dysfunction in the survey instrument which made Q10.2, Q16.7 invisible to respondents.<br><br>Please reach out to messamat@uw.edu for any question.
DOI: 10.34740/kaggle/dsv/2769160
title: UNET Lung Segmentation Weights for Chest X Rays
DOI: 10.6084/m9.figshare.16917691
title: screenspilot_dataset.xls

description: The dataset contains data screen media consumed during the SCREENS pilot trial (2018/2019). The data is used to evaluate the degree of compliance to two screen media use reduction interventions.
DOI: 10.5517/ccdc.csd.cc24vx97
title: CCDC 1992069: Experimental Crystal Structure Determination

description: Related Article: xiang xiangsh|2021|CSD Communication|||
description: Related Article: Jian-Hui Mao, Yong-Bin Wang, Limin Yang, Shao-Hua Xiang, Quan-Hao Wu, Yuan Cui, Qian Lu, Jie Lv, Shaoyu Li, Bin Tan|2021|Nature Chemistry|13|982|doi:10.1038/s41557-021-00750-x
DOI: 10.5517/ccdc.csd.cc285wt5
title: CCDC 2091037: Experimental Crystal Structure Determination

description: Related Article: Shicheng Wang, Dongming Zhang, Jinhua Zhu, Hongdong Liu, Bin Li, Luqi Huang|2021|J.Org.Chem.|86|12813|doi:10.1021/acs.joc.1c01447
description: Related Article: Shicheng Wang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc288rht
title: CCDC 2093786: Experimental Crystal Structure Determination

description: Related Article: Xiu-Gang Wu|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc288rkw
title: CCDC 2093788: Experimental Crystal Structure Determination

description: Related Article: Xiu-Gang Wu|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc288zxg
title: CCDC 2094016: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc288zyh
title: CCDC 2094017: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc288zzj
title: CCDC 2094018: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28900m
title: CCDC 2094019: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28901n
title: CCDC 2094020: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28902p
title: CCDC 2094021: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28903q
title: CCDC 2094022: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28904r
title: CCDC 2094023: Experimental Crystal Structure Determination

description: Related Article: Sheng Gao|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bbfd
title: CCDC 2095303: Experimental Crystal Structure Determination

description: Related Article: Pierre Baillargeon, Yves Dory, Tarik Rahem, Karl Lepitre, William Roy, Jonathan Santerre|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bbsr
title: CCDC 2095314: Experimental Crystal Structure Determination

description: Related Article: Pierre Baillargeon, Tarik Rahem, Marjolaine De Loof-Rochette, Mélanie Simard|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bhbg
title: CCDC 2095455: Experimental Crystal Structure Determination

description: Related Article: Arnold Rheingold, Ekkehard Sinn, Aruna Weerasinghe|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bj49
title: CCDC 2095480: Experimental Crystal Structure Determination

description: Related Article: Robin D. Rogers|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bjfl
title: CCDC 2095489: Experimental Crystal Structure Determination

description: Related Article: Anthony Avril, Jérémy Forté, Jamal Moussa|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28bpw6
title: CCDC 2095658: Experimental Crystal Structure Determination

description: Related Article: Erika Samolova|2021|CSD Communication|||
DOI: 10.6084/m9.figshare.15112737
title: Data from: Killer whale (Orcinus orca) population dynamics in response to a period of rapid ecosystem change in the eastern North Atlantic

description: This dataset contains the data files from the research article entitled "Killer whale (Orcinus orca) population dynamics in response to a period of rapid ecosystem change in the eastern North Atlantic". The files contain the capture histories of the individual killer whales photo-identified at herring wintering grounds in 1988-2019, and used for fitting capture-recapture models to estimate survival rates and abundance. All files can be imported directly into RMark and converted to .inp files to then fit models. The READ-ME.txt file provides a description for each data file.<br>
DOI: 10.6084/m9.figshare.15112737.v1
title: Data from: Dynamics of a killer whale (Orcinus orca) population in response to a period of rapid ecosystem change in the eastern North Atlantic.

description: This dataset contains the data files from the research article entitled "Dynamics of a killer whale (Orcinus orca) population in response to a period of rapid ecosystem change in the eastern North Atlantic. The files contains the capture histories of the individual killer whales photo-identified at herring wintering grounds in 1988-2019, and used for fitting capture-recapture models to estimate survival rates and abundance. All files can be imported directly into RMark and converted to .inp files to then fit models. The READ-ME.txt file provides a description for each data file.<br>
DOI: 10.5281/zenodo.5638549
title: SemEval-2010 Task 14: Word Sense Induction & Disambiguation

description: Data originally provided by the SemEval-2010 Task 14 organizers and which was available through the following links: 1. https://www.cs.york.ac.uk/semeval2010_WSI/files/evaluation.zip<br> 2. https://www.cs.york.ac.uk/semeval2010_WSI/files/training_data.tar.gz<br> 3. https://www.cs.york.ac.uk/semeval2010_WSI/files/test_data.tar.gz
DOI: 10.5281/zenodo.5638548
title: SemEval-2010 Task 14: Word Sense Induction & Disambiguation

description: Data originally provided by the SemEval-2010 Task 14 organizers and which was available through the following links: 1. https://www.cs.york.ac.uk/semeval2010_WSI/files/evaluation.zip<br> 2. https://www.cs.york.ac.uk/semeval2010_WSI/files/training_data.tar.gz<br> 3. https://www.cs.york.ac.uk/semeval2010_WSI/files/test_data.tar.gz
DOI: 10.5281/zenodo.5638551
title: Adiar 1.0.1 : Experiment Data

description: <strong>Adiar 1.0.1 Experimental Evaluation Data set</strong> You can here find the data set (and its analysis) created together with the experimental evaluation of the I/O-efficient BDD package Adiar as presented in the arXiv preprint https://arxiv.org/abs/2104.12101 In <em>raw.zip</em> you can find the raw console outputs from all the experiments. The analysis of these are split by topic into several <em>Libre Office </em><em>Calc</em> files (.odt). <strong>Cache</strong><br> Multiple experiments on <em>BuDDy</em>, <em>CUDD</em>, and <em>Sylvan</em> to expose how the I/O analysis manifests on the RAM-to-cache and Disk-to-RAM level. <strong>Equality Checking</strong><br> Timings for <em>Adiar</em> to perform equality checking for the Combinatorial Circuit benchmarks <strong>Optimisations</strong><br> Experiments on different versions of <em>Adiar</em> with and without the different optimisations. <strong>Reduce</strong><br> The <em>internal-arc to sink-arc </em>ratio on all the benchmarks run. <strong>Running Time</strong><br> The running time of <em>Adiar, BuDDy, CUDD, </em>and<em> Sylvan</em> to solve the different benchmarks. This is both on the comparable machine with 386 GiB of memory and 3.5 TiB of disk and also on another (semi-comparable) set of machines. <strong>Variable Memory</strong><br> Running time of <em>Adiar, CUDD, </em>and <em>Sylvan</em> when changing the amount of available memory. The file <em>License.txt</em> includes a <em>public domain</em> license for this data set.
DOI: 10.5281/zenodo.5638550
title: Adiar 1.0.1 : Experiment Data

description: <strong>Adiar 1.0.1 Experimental Evaluation Data set</strong> You can here find the data set (and its analysis) created together with the experimental evaluation of the I/O-efficient BDD package Adiar as presented in the arXiv preprint https://arxiv.org/abs/2104.12101 In <em>raw.zip</em> you can find the raw console outputs from all the experiments. The analysis of these are split by topic into several <em>Libre Office </em><em>Calc</em> files (.odt). <strong>Cache</strong><br> Multiple experiments on <em>BuDDy</em>, <em>CUDD</em>, and <em>Sylvan</em> to expose how the I/O analysis manifests on the RAM-to-cache and Disk-to-RAM level. <strong>Equality Checking</strong><br> Timings for <em>Adiar</em> to perform equality checking for the Combinatorial Circuit benchmarks <strong>Optimisations</strong><br> Experiments on different versions of <em>Adiar</em> with and without the different optimisations. <strong>Reduce</strong><br> The <em>internal-arc to sink-arc </em>ratio on all the benchmarks run. <strong>Running Time</strong><br> The running time of <em>Adiar, BuDDy, CUDD, </em>and<em> Sylvan</em> to solve the different benchmarks. This is both on the comparable machine with 386 GiB of memory and 3.5 TiB of disk and also on another (semi-comparable) set of machines. <strong>Variable Memory</strong><br> Running time of <em>Adiar, CUDD, </em>and <em>Sylvan</em> when changing the amount of available memory. The file <em>License.txt</em> includes a <em>public domain</em> license for this data set.
DOI: 10.48329/xtwg-gp32
title: CPRD GOLD HES A&E August 2021

description: HES Accident and Emergency (HES A&E) data consists of individual records of patient care administered in the accident and emergency setting in England. These data are a subset of national A&E data collected by NHS England to monitor the national standard that 95% of patients attending A&E should wait no longer than 4 hours from arrival to admission, transfer or discharge. A&E data are submitted by A&E providers of all types in England. Data collected includes details about patients’ attendance, outcomes of attendance, waiting times, referral source, A&E diagnosis, A&E treatment (drugs prescribed not recorded), A&E investigations and Health Resource Group. HES A&E may be used to clarify the health care pathway, to quantity health resource use and costs in the emergency setting, and to assess variations in the uptake of emergency services over time. Requests for HES A&E data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data. Coverage from April 2003 to March 2020.
DOI: 10.21252/d3fj-4m94
title: Draft DOI for ACS Nano Paper Submission 18 October 2021
DOI: 10.25411/aru.16903000
title: Inhibition of MUS81 by siRNA Reverses Resistance to Cisplatin in Human Ovarian Cancer Cell Lines.

description: I provide raw image files from an Imaging flow cytometer (ISX II). These files were used to provide estimate the cellular content of the endonuclease MuS81 following exposure of human cancer cell lines.This data was used in the submission to BMC Cancer of the manuscript:<br><b>Inhibition of MUS81 by siRNA Reverses Resistance to Cisplatin in Human Ovarian Cancer Cell Lines.</b> Emma C. Bourton<sup> </sup>Sheba Adam-Zahir, Piers N. Plowman, Hussein Nahidh Al-Ali, Helen A. Foster, Christopher N. Parris.<br><br>
DOI: 10.25411/aru.16903000.v1
title: Inhibition of MUS81 by siRNA Reverses Resistance to Cisplatin in Human Ovarian Cancer Cell Lines.

description: I provide raw image files from an Imaging flow cytometer (ISX II). These files were used to provide estimate the cellular content of the endonuclease MuS81 following exposure of human cancer cell lines.This data was used in the submission to BMC Cancer of the manuscript:<br><b>Inhibition of MUS81 by siRNA Reverses Resistance to Cisplatin in Human Ovarian Cancer Cell Lines.</b> Emma C. Bourton<sup> </sup>Sheba Adam-Zahir, Piers N. Plowman, Hussein Nahidh Al-Ali, Helen A. Foster, Christopher N. Parris.<br><br>
DOI: 10.48329/74nr-h920
title: CPRD GOLD RTDS August 2021

description: Cancer data contain data provided by Public Health England (PHE) via the National Cancer Registration and Analysis Service (NCRAS). Linked NCRAS CPRD datasets include the National Radiotherapy Dataset (RTDS) dataset which contains records of radiotherapy services provided since April 2009, including teletherapy and brachytherapy. All radiotherapy delivered in England to patients in NHS facilities, or in private facilities where delivery was funded by the NHS, is included. Brachytherapy delivered for the treatment of non-malignant disease, radiotherapy delivered using unsealed sources, and non-therapeutic exposures delivered using radiotherapy machines (e.g. imaging) are not included. NCRAS data are subject to additional data governance requirements and any researcher proposing to use these data should discuss their NCRAS requirements with CPRD’s Observational Research team prior to protocol submission. Requests for NCRAS Cancer Registration data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data. Coverage is for patients with tumours recorded in the cancer registration data from April 2021 to December 2018.
DOI: 10.48329/4jwp-4951
title: CPRD GOLD SACT August 2021

description: Cancer data contain data provided by Public Health England (PHE) via the National Cancer Registration and Analysis Service (NCRAS). Linked NCRAS CPRD datasets include the Systemic Anti-Cancer Treatment (SACT) dataset covering chemotherapy treatment for all solid tumour and haematological malignancies, including those in clinical trials. Information is included about programme and regime of treatment, and the outcome for each treatment. NCRAS data are subject to additional data governance requirements and any researcher proposing to use these data should discuss their NCRAS requirements with CPRD’s Observational Research team prior to protocol submission. Requests for NCRAS Cancer Registration data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data. Coverage is for patients with tumours recorded in the cancer registration data from January 2014 to December 2018.
DOI: 10.48329/541y-nh70
title: CPRD GOLD Cancer Registration August 2021

description: Cancer data contain data provided by Public Health England (PHE) via the National Cancer Registration and Analysis Service (NCRAS). Linked NCRAS CPRD datasets include Cancer Registration data which contains a record for each registrable tumour diagnosed or treated in England, of which the NCRAS has been notified. Cancers are coded using the International Classification of Diseases for Oncology, revision 3, 2011. They are also back mapped to the tenth revision of the International Classification of Diseases version 10. NCRAS data are subject to additional data governance requirements and any researcher proposing to use these data should discuss their NCRAS requirements with CPRD’s Observational Research team prior to protocol submission. Requests for NCRAS Cancer Registration data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data. Coverage for cancer registrations from January 1990 to December 2018.
DOI: 10.48329/xjqf-ag80
title: CPRD GOLD HES DID August 2021

description: The Diagnostic Imaging Dataset (DID) is a collection of detailed information about diagnostic imaging tests, such as x-rays and MRI scans, taken from NHS providers' radiological information systems. The DID includes information on imaging tests carried out from 1 April 2012 on NHS patients in England. It does not include the images that are produced as a result of these tests. The DID captures information about referral source and patient type, details of the test (type of test and body site), plus items about waiting times for each diagnostic imaging event, from time of test request through to time of reporting. The DID enables analysis of demographic and geographic variation in access to different test types and different providers. Requests for HES DID data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data. Coverage from April 2012 to October 2020.
DOI: 10.48329/hs74-2d25
title: CPRD Aurum RTDS August 2021

description: Cancer data contain data provided by Public Health England (PHE) via the National Cancer Registration and Analysis Service (NCRAS). Linked NCRAS CPRD datasets include the National Radiotherapy Dataset (RTDS) dataset which contains records of radiotherapy services provided since April 2009, including teletherapy and brachytherapy. All radiotherapy delivered in England to patients in NHS facilities, or in private facilities where delivery was funded by the NHS, is included. Brachytherapy delivered for the treatment of non-malignant disease, radiotherapy delivered using unsealed sources, and non-therapeutic exposures delivered using radiotherapy machines (e.g. imaging) are not included. 
NCRAS data are subject to additional data governance requirements and any researcher proposing to use these data should discuss their NCRAS requirements with CPRD’s Observational Research team prior to protocol submission.
Requests for NCRAS Cancer Registration data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data.
Coverage is for patients with tumours recorded in the cancer registration data from April 2021 to December 2018.
DOI: 10.48329/ngt7-ex36
title: CPRD Aurum SACT August 2021

description: Cancer data contain data provided by Public Health England (PHE) via the National Cancer Registration and Analysis Service (NCRAS). Linked NCRAS CPRD datasets include the Systemic Anti-Cancer Treatment (SACT) dataset covering chemotherapy treatment for all solid tumour and haematological malignancies, including those in clinical trials. Information is included about programme and regime of treatment, and the outcome for each treatment. 
NCRAS data are subject to additional data governance requirements and any researcher proposing to use these data should discuss their NCRAS requirements with CPRD’s Observational Research team prior to protocol submission.
Requests for NCRAS Cancer Registration data access are subject to prior protocol approval. Further information is available at https://www.cprd.com/linked-data.
Coverage is for patients with tumours recorded in the cancer registration data from January 2014 to December 2018.