cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1003857.v4
title: Data for: "Forgotten treasures: the fate of data in animal behavior studies"

description: Supporting material for the article. Please refer to the file 'read_me.txt' for detailed information of each file in the dataset. <strong>Abstract.</strong> Published discussions on data stewardship often focus on standardized datasets whose reuse patterns are known. Improvements in stewardship of animal behavior data are virtually absent and lag behind other disciplines such as molecular biology and systematics. In this essay, we discuss best practices of three key aspects related to the collection and archival of behavioral data: data supporting published results; data collected from field observations; and the potential of museum specimens as source of data to animal behavior and ecology. To quantify how much data is shared in animal behavior publications we reviewed articles published in 2013 and found that an extremely small proportion of the articles made even part of their data available. We discuss about the benefits of making data available, review resources available for data archiving and provide practical guidance for ethologists. We discuss and provide examples of the amount of ethological and ecological data that can be recorded during field observations. To investigate the potential of museum specimens as source of data, we surveyed researchers working in areas related to ecology, animal behavior, and systematics. Both ethologists and systematists agreed that natural history information stored in collections would be a valuable source of data. We make recommendations to enhance data collection and stewardship from the point of view of researchers in animal behavior sciences, considering the special characteristics of the discipline and the type of data that is often produced. We suggest that there is a large amount of crucial data about natural history, ecology and behavior that investigators could glean from collections. Although it is difficult to appreciate the relevance of data for future studies at the time of publication, such data may inspire fruitful opportunities that we cannot afford to lose.
DOI: 10.6084/m9.figshare.1003835.v2
title: GRAD 521 Research Data Management Lectures

description: This is a series of lectures from a 10-week, 2-credit graduate-level course in research data management. <br><br>The course description is: "Careful examination of all aspects of research data management best practices. Designed to prepare students to exceed funder mandates for performance in data planning, documentation, preservation and sharing in an increasingly complex digital research environment. Open to students of all disciplines." <br><br>Major course content includes: Overview of research data management, definitions and best practices; Types, formats and stages of research data; Metadata (data documentation); Data storage, backup and security; Legal and ethical considerations of research data; Data sharing and reuse; Archiving and preservation. <br><br>The course was offered for the first time during the Winter 2014 term (January - March). See the associated syllabus, lesson plans and assignments.
DOI: 10.6084/m9.figshare.1003857.v5
title: Data for: "Forgotten treasures: the fate of data in animal behavior studies"

description: Supporting material for the article. Please refer to the file 'read_me.txt' for detailed information of each file in the dataset. <strong>Abstract.</strong> Published discussions on data stewardship often focus on standardized datasets whose reuse patterns are known. Improvements in stewardship of animal behavior data are virtually absent and lag behind other disciplines such as molecular biology and systematics. In this essay, we discuss best practices of three key aspects related to the collection and archival of behavioral data: data supporting published results; data collected from field observations; and the potential of museum specimens as source of data to animal behavior and ecology. To quantify how much data is shared in animal behavior publications we reviewed articles published in 2013 and found that an extremely small proportion of the articles made even part of their data available. We discuss about the benefits of making data available, review resources available for data archiving and provide practical guidance for ethologists. We discuss and provide examples of the amount of ethological and ecological data that can be recorded during field observations. To investigate the potential of museum specimens as source of data, we surveyed researchers working in areas related to ecology, animal behavior, and systematics. Both ethologists and systematists agreed that natural history information stored in collections would be a valuable source of data. We make recommendations to enhance data collection and stewardship from the point of view of researchers in animal behavior sciences, considering the special characteristics of the discipline and the type of data that is often produced. We suggest that there is a large amount of crucial data about natural history, ecology and behavior that investigators could glean from collections. Although it is difficult to appreciate the relevance of data for future studies at the time of publication, such data may inspire fruitful opportunities that we cannot afford to lose.
DOI: 10.6084/m9.figshare.1003834.v1
title: GRAD 521 Research Data Management Syllabus and Lesson Plans

description: These are the syllabus and lesson plans for a series of lectures from a 10-week, 2-credit graduate-level course in research data management. The course description is: "Careful examination of all aspects of research data management best practices. Designed to prepare students to exceed funder mandates for performance in data planning, documentation, preservation and sharing in an increasingly complex digital research environment. Open to students of all disciplines." Major course content includes: Overview of research data management, definitions and best practices; Types, formats and stages of research data; Metadata (data documentation); Data storage, backup and security; Legal and ethical considerations of research data; Data sharing and reuse; Archiving and preservation. The course was offered for the first time during the Winter 2014 term (January - March). See the associated lectures and assignments.
DOI: 10.6084/m9.figshare.1003835.v1
title: GRAD521 Research Data Management Lectures

description: This is a series of lectures from a 10-week, 2-credit graduate-level course in research data management. <br><br>The course description is: "Careful examination of all aspects of research data management best practices. Designed to prepare students to exceed funder mandates for performance in data planning, documentation, preservation and sharing in an increasingly complex digital research environment. Open to students of all disciplines." <br><br>Major course content includes: Overview of research data management, definitions and best practices; Types, formats and stages of research data; Metadata (data documentation); Data storage, backup and security; Legal and ethical considerations of research data; Data sharing and reuse; Archiving and preservation. <br><br>The course was offered for the first time during the Winter 2014 term (January - March). See the associated syllabus, lesson plans and assignments.
DOI: 10.6084/m9.figshare.1003857.v7
title: Data for: "Forgotten treasures: the fate of data in animal behavior studies"

description: Supporting material for the article. Please refer to the file 'read_me_metadata.txt' for detailed information (i.e., metadata) of each file in the dataset. <strong>Abstract. </strong>The majority of publications across many disciplines in biology do not make their data available in repositories. On the other hand, there are several advantages associated with archiving data in open access repositories and technological resources are available to do so. To date no study has estimated the frequency of data from animal behavior publications made available in digital repositories or supplementary materials. In order to evaluate how much data from those studies are available, we surveyed publications from two well-known journals in the field. Since journal policy is an important factor influencing the availability of data from publications, we listed the data policy of journals that publish animal behavior research. We found that only a small proportion of the articles published in 2013 made even part of their data available and journals do not require data to be archived prior or after publication. If not deposited in repositories, data supporting those findings will most likely be lost due to lack of usage, inability to access obsolete storage devices or even the death of the authors. Although it is difficult to appreciate the relevance of data for future studies at the time of a research article's publication, such data may inspire fruitful opportunities that we cannot afford to lose. We discuss the benefits of making data available, review resources for data archiving and provide practical guidelines. We hope that raising awareness about this problem will help foster a data sharing culture among animal behaviorists.
DOI: 10.6084/m9.figshare.1003793
title: Dataset VU Angewandte GIS Grundlagen

description: Daten zu den Aufgaben aus der VU Angewandte GIS -Grundlagen. http://openscienceasap.org/education/courses/vu-angewandte-gis-grundlagen/ https://github.com/skasberger/vu-angewandte-gis-grundlagen
DOI: 10.6084/m9.figshare.1003857.v6
title: Data for: "Forgotten treasures: the fate of data in animal behavior studies"

description: Supporting material for the article. Please refer to the file 'read_me.txt' for detailed information of each file in the dataset. <strong>Abstract.</strong> Published discussions on data stewardship often focus on standardized datasets whose reuse patterns are known. Improvements in stewardship of animal behavior data are virtually absent and lag behind other disciplines such as molecular biology and systematics. In this essay, we discuss best practices of three key aspects related to the collection and archival of behavioral data: data supporting published results; data collected from field observations; and the potential of museum specimens as source of data to animal behavior and ecology. To quantify how much data is shared in animal behavior publications we reviewed articles published in 2013 and found that an extremely small proportion of the articles made even part of their data available. We discuss about the benefits of making data available, review resources available for data archiving and provide practical guidance for ethologists. We discuss and provide examples of the amount of ethological and ecological data that can be recorded during field observations. To investigate the potential of museum specimens as source of data, we surveyed researchers working in areas related to ecology, animal behavior, and systematics. Both ethologists and systematists agreed that natural history information stored in collections would be a valuable source of data. We make recommendations to enhance data collection and stewardship from the point of view of researchers in animal behavior sciences, considering the special characteristics of the discipline and the type of data that is often produced. We suggest that there is a large amount of crucial data about natural history, ecology and behavior that investigators could glean from collections. Although it is difficult to appreciate the relevance of data for future studies at the time of publication, such data may inspire fruitful opportunities that we cannot afford to lose.
DOI: 10.6084/m9.figshare.1003779
title: Debris items with associated taxa (Supplementary Table 1)

description: This is an author-generated, self-archived version. The final publication is available at link.springer.com. DOI: 10.1007/s00227-014-2432-8 Link: http://link.springer.com/article/10.1007/s00227-014-2432-8 Bibliographic info: Goldstein, M.C., H.S. Carson, and M. Eriksen. 2014. Relationship of diversity and habitat area in North Pacific plastic-associated rafting communities. Marine Biology, published online 13 April 2014. DOI: 10.1007/s00227-014-2432-8.
DOI: 10.6084/m9.figshare.1003781
title: Instrumento libre para Medición en los Labaratorios

description: El proyecto consiste en desarrollar una herramienta libre (en Hardware y Software) usando una Raspberry Pi, en la cual se le pueda conectar cualquier tipo de sensor y poder realizar un control mediante internet. Se hace uso de las siguientes herramientas: Python, Flask, Chaco, StatsModels, RPI.GPIO, Numpy
DOI: 10.6084/m9.figshare.1003793.v1
title: Dataset VU Angewandte GIS Grundlagen

description: Daten zu den Aufgaben aus der VU Angewandte GIS -Grundlagen. http://openscienceasap.org/education/courses/vu-angewandte-gis-grundlagen/ https://github.com/skasberger/vu-angewandte-gis-grundlagen
DOI: 10.6084/m9.figshare.1003780
title: Relationship of diversity and habitat area in North Pacific plastic-associated rafting communities

description: This is an author-generated, self-archived version. The final publication is available at link.springer.com. DOI: 10.1007/s00227-014-2432-8 Link: http://link.springer.com/article/10.1007/s00227-014-2432-8 Bibliographic info: Goldstein, M.C., H.S. Carson, and M. Eriksen. 2014. Relationship of diversity and habitat area in North Pacific plastic-associated rafting communities. Marine Biology, published online 13 April 2014. DOI: 10.1007/s00227-014-2432-8.
DOI: 10.6084/m9.figshare.1003781.v1
title: Instrumento libre para Medición en los Labaratorios

description: El proyecto consiste en desarrollar una herramienta libre (en Hardware y Software) usando una Raspberry Pi, en la cual se le pueda conectar cualquier tipo de sensor y poder realizar un control mediante internet. Se hace uso de las siguientes herramientas: Python, Flask, Chaco, StatsModels, RPI.GPIO, Numpy
DOI: 10.6084/m9.figshare.1003755
title: SNOW 2014 Data Challenge

description: Resources and data from the SNOW 2014 Data Challenge. If you use these resources for your research, please cite: Symeon Papadopoulos, David Corney, Luca Aiello (2014). SNOW 2014 Data Challenge: Assessing the Performance of News Topic Detection Methods in Social Media. <em>Proceedings of the SNOW 2014 Data Challenge</em>, April 2014 For more information see: http://www.socialsensor.eu/use-cases/evaluation/122-snow2014-data-challenge
DOI: 10.6084/m9.figshare.1002167
title: Beads convolution/deconvolution simulation

description: Simulation of beads acquired with a 100x / 1.4 NA objective, the pixel size is 65 nm and the Z spacing is 200 nm. This is a simple "pixelated" simulation. Beads were 3 to 4 voxels laterally and 1 voxel axially. They were convolved with a PSF generated using the above parameters and assuming an embedding media of RI=1.4 and a depth below coverslip of 1 micron. Simulated phantom was convolved with PSF to produce a simluated "image", then deconvolved with 200 iterations of noncirculant Richardson Lucy. Low level code was written in Java (deconvolution, psf generation). High level code was written in Jython and can be found here - https://github.com/bnorthan/projects/tree/master/Scripts/Jython.
DOI: 10.6084/m9.figshare.1002142
title: Deconvolved Bead Image

description: Deconvolved bead image. Original dataset was acquired by Kurt Thorn UCSF and is in 100xPSF_deconvolved_nc_200.ome.tif.zip. Deconvolved using 200 iterations of non-circulant Richardson Lucy. The PSF was generated using COSMOS software using the Gibson Lanni method using 1.4 NA, the pixel size is 65 nm and the Z spacing is 200 nm, sample RI of 1.4, and depth of 1 micron. Code was implemented as Image2 plugins and can be found here: https://github.com/bnorthan/projects.
DOI: 10.6084/m9.figshare.1002167.v1
title: Beads convolution/deconvolution simulation

description: Simulation of beads acquired with a 100x / 1.4 NA objective, the pixel size is 65 nm and the Z spacing is 200 nm. This is a simple "pixelated" simulation. Beads were 3 to 4 voxels laterally and 1 voxel axially. They were convolved with a PSF generated using the above parameters and assuming an embedding media of RI=1.4 and a depth below coverslip of 1 micron. Simulated phantom was convolved with PSF to produce a simluated "image", then deconvolved with 200 iterations of noncirculant Richardson Lucy. Low level code was written in Java (deconvolution, psf generation). High level code was written in Jython and can be found here - https://github.com/bnorthan/projects/tree/master/Scripts/Jython.
DOI: 10.6084/m9.figshare.1003755.v1
title: SNOW 2014 Data Challenge

description: Resources and data from the SNOW 2014 Data Challenge. If you use these resources for your research, please cite: Symeon Papadopoulos, David Corney, Luca Aiello (2014). SNOW 2014 Data Challenge: Assessing the Performance of News Topic Detection Methods in Social Media. <em>Proceedings of the SNOW 2014 Data Challenge</em>, April 2014 For more information see: http://www.socialsensor.eu/use-cases/evaluation/122-snow2014-data-challenge
DOI: 10.6084/m9.figshare.1002139
title: Bead Image

description: Bead image acquired by Kurt Thorn USCF. acquired with a 100x / 1.4 NA objective, the pixel size is 65 nm and the Z spacing is 200 nm
DOI: 10.6084/m9.figshare.1002142.v1
title: Deconvolved Bead Image

description: Deconvolved bead image. Original dataset was acquired by Kurt Thorn UCSF and is in 100xPSF_deconvolved_nc_200.ome.tif.zip. Deconvolved using 200 iterations of non-circulant Richardson Lucy. The PSF was generated using COSMOS software using the Gibson Lanni method using 1.4 NA, the pixel size is 65 nm and the Z spacing is 200 nm, sample RI of 1.4, and depth of 1 micron. Code was implemented as Image2 plugins and can be found here: https://github.com/bnorthan/projects.
DOI: 10.6084/m9.figshare.1003755.v3
title: SNOW 2014 Data Challenge

description: Resources and data from the SNOW 2014 Data Challenge. If you use these resources for your research, please cite: Symeon Papadopoulos, David Corney, Luca Aiello (2014). SNOW 2014 Data Challenge: Assessing the Performance of News Topic Detection Methods in Social Media. <em>Proceedings of the SNOW 2014 Data Challenge</em>, April 2014 For more information see: http://www.socialsensor.eu/use-cases/evaluation/122-snow2014-data-challenge
DOI: 10.6084/m9.figshare.1002139.v1
title: Bead Image

description: Bead image acquired by Kurt Thorn USCF. acquired with a 100x / 1.4 NA objective, the pixel size is 65 nm and the Z spacing is 200 nm
DOI: 10.6084/m9.figshare.1003755.v2
title: SNOW 2014 Data Challenge

description: Resources and data from the SNOW 2014 Data Challenge. If you use these resources for your research, please cite: Symeon Papadopoulos, David Corney, Luca Aiello (2014). SNOW 2014 Data Challenge: Assessing the Performance of News Topic Detection Methods in Social Media. <em>Proceedings of the SNOW 2014 Data Challenge</em>, April 2014 For more information see: http://www.socialsensor.eu/use-cases/evaluation/122-snow2014-data-challenge
DOI: 10.7925/drs1.duchas_5106932
title: Old Crafts

description: Story collected by a student at Rathregan school (Rathregan, Co. Meath) from informant John Bannon.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Uigín.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5106933
title: Local Happenings

description: Story collected by Marie Lovely, a student at Rathregan school (Rathregan, Co. Meath) from informant Mrs Lovely.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Uigín.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5120300
title: Care of the Feet

description: Story collected by Michael Healy, a student at Walshestown school (Walshestown North, Co. Westmeath) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Bean Uí Dhuibhir.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5130006
title: Care of the Feet

description: Story collected by James O Neill, a student at Ballykelly school (Ballykelly, Co. Wexford) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Pádraig Mac Uadain.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4782595
title: Herbs

description: Story collected by Peter Smyth, a student at Tattenclave school (Tattintlieve, Co. Monaghan) from informant Peter Carroll.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Bríd Ní Chróinín.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5106934
title: Old Crafts

description: Story collected by Marie Lovely, a student at Rathregan school (Rathregan, Co. Meath) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Máire, Bean Uí Uigín.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5120301
title: Local Forge

description: Story collected by Philomena Healy, a student at Walshestown school (Walshestown North, Co. Westmeath) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Bean Uí Dhuibhir.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_5130007
title: Local Forges

description: Story collected by John Hearn, a student at Ballykelly school (Ballykelly, Co. Wexford) (no informant identified).
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Pádraig Mac Uadain.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4782601
title: Herbs

description: Story collected by Frank Moyna, a student at Tattenclave school (Tattintlieve, Co. Monaghan) from informant Frank Moyna.
description: Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Bríd Ní Chróinín.
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.