cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.91145.v1
title: Correlations among network and community structure metrics

description: Kerri Crawford, now a postdoc at Washington University St. Louis, and I were writing a paper about correlations among network and community structures - an attempt to think more explicitly about these two fields. We include our paper that we submitted to Oikos, and was rejected. Upon further thinking about this, I don't know if the paper even makes sense! Figure captions: Figure 1. Correlations among network structural properties (ordinate) and species richness (abscissa) for animals and plants. Plant-pollinator (empty circles) and plant-seed disperser (filled circles) mutualistic networks are represented. Network structures: number of links (a,b), links per species (c,d), nestedness (e,f), and connectance (g,h; see Table 1 for definitions). Values in each panel represent Pearson correlation coefficients, and p-values (H<sub>o</sub>, <em>r</em> = 0). All variables were log<sub>10</sub> transformed prior to analysis. Note that all variables are displayed as log<sub>10</sub> transformed. Sample sizes: species richness (58-59 communities); evenness (20 communities). Data from the Interaction Web Database (http://www.nceas.ucsb.edu/interactionweb/), and Rezende <em>et al</em>. (2007). Figure 2. Correlations among network structural properties (ordinate) and evenness (abscissa) for animals and plants. Evenness (Pielou’s J) is constrained between zero and one. Larger values of J represent communities with abundance spread more equally among species, whereas small J values represent the presence of few very abundant species. See Figure 1 caption for details on figures. Figure 3. Correlations among network structural properties (ordinate) and mean and standard deviation of the log normal distribution fit to abundance data for each community (abscissa) for animals. See Figure 1 caption for details on figures, and Appendix 1 for abundance distribution model results. Figure 4. Correlations among network structural properties (ordinate) and mean and standard deviation of the log normal distribution fit to abundance data for each community (abscissa) for plants. See Figure 1 caption for details on figures, and Appendix 1 for abundance distribution model results.
DOI: 10.6084/m9.figshare.91147.v1
title: Ruminant Outlines

description: Digitised snout profile outlines for a large sample of extant ruminants. All specimens are from the Zoology Department at the Natural History Museum, London. Scales are not present, as the intention was to analyse the geometry independent of the size variable.
DOI: 10.6084/m9.figshare.91140
title: Tobacco Seed Growth in 66% D2O Trial 1

description: These are the pictures of tobacco seed growth in 66% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91142
title: Tobacco Growth in 99% D2O Trial 1

description: These are the pictures of tobacco seed growth in 99% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91135
title: Tobacco Seed Growth in 33% D2O Trial 1

description: These are the pictures of tobacco seed growth in 33% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91140.v1
title: Tobacco Seed Growth in 66% D2O Trial 1

description: These are the pictures of tobacco seed growth in 66% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91142.v1
title: Tobacco Growth in 99% D2O Trial 1

description: These are the pictures of tobacco seed growth in 99% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91135.v1
title: Tobacco Seed Growth in 33% D2O Trial 1

description: These are the pictures of tobacco seed growth in 33% D2O mixed with di water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91132
title: Tobacco Seed Growth in DDW Trial 1

description: These are the pictures of tobacco seed growth in 99.9% deuterium depleted water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91133
title: Tobacco Seed Growth in DI Water Trial 1

description: These are the pictures of tobacco seed growth in deionized water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91132.v1
title: Tobacco Seed Growth in DDW Trial 1

description: These are the pictures of tobacco seed growth in 99.9% deuterium depleted water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.90841
title: CRAM Artificial Metagenomes

description: Several artificial metagenomes created to benchmark a metagenome annotation pipeline. Combined Tables.zip contains matrices with the number of reads belonging to each identified subsystem across all samples.
DOI: 10.6084/m9.figshare.91133.v2
title: Tobacco Seed Growth in DI Water Trial 1

description: These are the pictures of tobacco seed growth in deionized water. Pictures are taken once every 24 hours. The higher the number in the image name, the later in time that picture was taken. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.91133.v1
title: Tobacco Seed Growth in DI Water

description: See the links below for information about the experiment. These are the pictures of tobacco seed growth in deionized water. Data, slideshows, and experiment background and information can be found through the links below.
DOI: 10.6084/m9.figshare.90841.v2
title: CRAM Artificial Metagenomes

description: Several artificial metagenomes created to benchmark a metagenome annotation pipeline. Combined Tables.zip contains matrices with the number of reads belonging to each identified subsystem across all samples.
DOI: 10.6084/m9.figshare.90828
title: CrowdoMeter Tweets

description: 467 tweets that contain links to scholarly content, collected in October 2011. Analyzed in the CrowdoMeter project.
DOI: 10.6084/m9.figshare.90818
title: SciFund Success and Social Media

description: SciFund results and data were discussed partly by Zen Faulkes, who also led a succesfully funded project, at http://neurodojo.blogspot.com/2011/12/sayonara-scifund.html and in social media such as in this comment, "Funding was correlated to likes on Facebook" in https://twitter.com/#!/DoctorZen/status/169213149759807488. Data were shared via a Google Document at the link below and had been compiled from public sources. <strong>About SciFund: The #SciFund Challenge raised over <strong>$75,000</strong> for science, from 1440 contributors! </strong> <strong></strong><strong>What?</strong> Can scientists raise money for their research by convincing the general public to open their wallets for small-amount donations? The process is called crowdfunding. <strong>Who?</strong> Forty-nine scientists from a wide variety of disciplines (ecology to computer science to applied math) in five countries signed on to crowdfund their research. <strong>When?</strong> November 1-December 15, 2011. <strong>Where?</strong> The #SciFund Challenge was run through RocketHub, http://www.rockethub.com/projects/scifund a major crowdfunding platform on the Internet. A blog was the community hub for the Challenge, http://scifund.wordpress.com/.
DOI: 10.6084/m9.figshare.90828.v1
title: CrowdoMeter Tweets

description: 467 tweets that contain links to scholarly content, collected in October 2011. Analyzed in the CrowdoMeter project.
DOI: 10.6084/m9.figshare.90829
title: CrowdoMeter Tweet Classifications

description: 953 classifications of 467 tweets from Crowdometer.org that contain links to scholarly content, collected in October 2011.
DOI: 10.6084/m9.figshare.90841.v1
title: CRAM Artificial Metagenomes

description: Several artificial metagenomes created to benchmark a metagenome annotation pipeline.
DOI: 10.6084/m9.figshare.90235
title: Research data services at White Rose Research Online - Questionnaire data

description: This study, inspired by Tony Hey’s “The Data Deluge”, was carried out to discover whether the Institutional Repository is a suitable body to manage curation of and access to the source data created at the institution. This study surveyed research scientists at the White Rose Universities to discover their practices of and attitudes to research data storage, sharing and publication. Key role players in the research data management process were interviewed to investigate possible options for a data infrastructure, the capabilities of WRRO, the establishment of a discipline-based repository and issues of metadata assignment.
DOI: 10.6084/m9.figshare.90804
title: Contiguous sequences from Vibrio tubiashii ATCC19106 assembly

description: Contiguous sequences from <em>de novo</em> assembly of <em>V. tubiashii</em> strain ATCC19106.
DOI: 10.6084/m9.figshare.90805
title: Contiguous sequences from Vibrio tubiashii RE22 assembly

description: Contiguous sequences from <em>de novo</em> assembly of <em>V. tubiashii,</em> strain RE22.
DOI: 10.6084/m9.figshare.90234
title: Tweets linking to scientific papers - Jul 2011

description: This dataset lists the ~ 58k tweets that mentioned a scientific article (broadly speaking anything with a DOI, PMID or arxiv ID) between the 1st and 31st of July 2011. Recall isn’t 100%: my best estimate is that it’s missing another ~ 6k tweets where the article couldn’t be identified, the link was malformed or the journal involved is new or gets very low traffic. Twitter’s TOS prohibit re-distribution of the tweets themselves but the dataset contains the extracted links, the tweet ID and some information about the tweeter (screen name, country & lat/lng derived from their location using Yahoo! Placemaker). The links, pmids, dois and arxiv_ids columns can contain more than one value are are pipe (|) delimited. If you use this dataset please credit http://www.altmetric.com somewhere – doesn’t need to be a prominent link or a graphic or anything, some text tucked away on an about page will do!
DOI: 10.6084/m9.figshare.90805.v2
title: Contiguous sequences from Vibrio tubiashii RE22 assembly

description: Contiguous sequences from <em>de novo</em> assembly of <em>V. tubiashii,</em> strain RE22.
DOI: 10.6084/m9.figshare.90234.v1
title: Tweets linking to scientific papers - Jul 2011

description: This dataset lists the ~ 58k tweets that mentioned a scientific article (broadly speaking anything with a DOI, PMID or arxiv ID) between the 1st and 31st of July 2011. Recall isn’t 100%: my best estimate is that it’s missing another ~ 6k tweets where the article couldn’t be identified, the link was malformed or the journal involved is new or gets very low traffic. Twitter’s TOS prohibit re-distribution of the tweets themselves but the dataset contains the extracted links, the tweet ID and some information about the tweeter (screen name, country & lat/lng derived from their location using Yahoo! Placemaker). The links, pmids, dois and arxiv_ids columns can contain more than one value are are pipe (|) delimited. If you use this dataset please credit http://www.altmetric.com somewhere – doesn’t need to be a prominent link or a graphic or anything, some text tucked away on an about page will do!
DOI: 10.6084/m9.figshare.90804.v2
title: Contiguous sequences from Vibrio tubiashii ATCC19106 assembly

description: Contiguous sequences from <em>de novo</em> assembly of <em>V. tubiashii</em> strain ATCC19106.
DOI: 10.6084/m9.figshare.90218
title: FTIR spectra DDW, DI, D20 raw data 2-2-2012

description: FTIR spectroscopy 2-2-2012 We examined 5 samples (3mL of each), plus an empty cuvette for background: empty cuvette (background): DARK BLUE DDW: DARK PURPLE (hard to see) DDW + 1uL D2O (roughly equivalent to SMOW): GREEN DDW + 70uL D2O (because the 1uL looked so close to DDW): LIGHT BLUE DI: LIGHT PURPLE D2O: RED
DOI: 10.6084/m9.figshare.90235.v1
title: Research data services at White Rose Research Online

description: This study, inspired by Tony Hey’s “The Data Deluge”, was carried out to discover whether the Institutional Repository is a suitable body to manage curation of and access to the source data created at the institution. This study surveyed research scientists at the White Rose Universities to discover their practices of and attitudes to research data storage, sharing and publication. Key role players in the research data management process were interviewed to investigate possible options for a data infrastructure, the capabilities of WRRO, the establishment of a discipline-based repository and issues of metadata assignment.
DOI: 10.6084/m9.figshare.90804.v1
title: Contigs_de_novo_ATCC_19106

description: de novo assembly of V. tubiashii strain ATCC19106
DOI: 10.6084/m9.figshare.90218.v1
title: FTIR spectra DDW, DI, D20 raw data 2-2-2012

description: FTIR spectroscopy 2-2-2012 We examined 5 samples (3mL of each), plus an empty cuvette for background: empty cuvette (background): DARK BLUE DDW: DARK PURPLE (hard to see) DDW + 1uL D2O (roughly equivalent to SMOW): GREEN DDW + 70uL D2O (because the 1uL looked so close to DDW): LIGHT BLUE DI: LIGHT PURPLE D2O: RED
DOI: 10.6084/m9.figshare.90805.v1
title: Contigs_de_novo_RE22

description: de novo assembly of <em>V. tubiashii</em> RE22
DOI: 10.6084/m9.figshare.90235.v3
title: Research data services at White Rose Research Online - Questionnaire data

description: This study, inspired by Tony Hey’s “The Data Deluge”, was carried out to discover whether the Institutional Repository is a suitable body to manage curation of and access to the source data created at the institution. This study surveyed research scientists at the White Rose Universities to discover their practices of and attitudes to research data storage, sharing and publication. Key role players in the research data management process were interviewed to investigate possible options for a data infrastructure, the capabilities of WRRO, the establishment of a discipline-based repository and issues of metadata assignment.
DOI: 10.6084/m9.figshare.90213
title: Does more CO2 improve phytoplankton growth in culture?

description: We noticed that the Pseudo-nitzschia delicatissima (strain LaPn-4) cultures were growing better than expected. We speculated that the culture’s growth suddenly improved because it was getting more CO2 than before. We reached this conclusion because: 1. The culture grew better as flasks were changed more frequently 2. The culture grew better as the flasks we kept them in increased in volume 3. The culture was in flasks and had to be poured to take fluorometer readings and to do dilutions To investigate this, we used three 100mL cultures in 250mL Erlenmeyer flasks. F-28 was aerated using a pasteur pipette attached with rubber tubing and airline hose to an aquarium pump. The volumes needed for measurements and dilutions were removed and added using a sterile pipette. F-27 was not aerated. In order to take measurements and dilute the appropriate volume was pipetted in and out of the flask. F-26 was not aerated either. In order to obtain culture for measurements and dilutions the appropriate volume was poured into and out of the flask. No pipettes were used. All flasks were shaken to suspend cells evenly before fluorescence measurements were taken. Later, upon comparing the length of the cells in the same culture of the previous year, we noticed that the cells were significantly longer this year. This told us that the increased growth, health, and chain length was due to the culture undergoing sexual reproduction. Chain length for F-28 was numerous at 4-8 cells per chain while both the pipetted and poured culture was most numerous at 1-2 cells per chain. Cell length was about 57 m in length and was uniform over the three flasks. I used an epifluorescent microscope to count and measure the cells. Guidelines that I used: 1. Count at least 100 chains 2. Dividing cells count as one cell in the chain
DOI: 10.6084/m9.figshare.90213.v1
title: Does more CO2 improve phytoplankton growth in culture?

description: We noticed that the Pseudo-nitzschia delicatissima (strain LaPn-4) cultures were growing better than expected. We speculated that the culture’s growth suddenly improved because it was getting more CO2 than before. We reached this conclusion because: 1. The culture grew better as flasks were changed more frequently 2. The culture grew better as the flasks we kept them in increased in volume 3. The culture was in flasks and had to be poured to take fluorometer readings and to do dilutions To investigate this, we used three 100mL cultures in 250mL Erlenmeyer flasks. F-28 was aerated using a pasteur pipette attached with rubber tubing and airline hose to an aquarium pump. The volumes needed for measurements and dilutions were removed and added using a sterile pipette. F-27 was not aerated. In order to take measurements and dilute the appropriate volume was pipetted in and out of the flask. F-26 was not aerated either. In order to obtain culture for measurements and dilutions the appropriate volume was poured into and out of the flask. No pipettes were used. All flasks were shaken to suspend cells evenly before fluorescence measurements were taken. Later, upon comparing the length of the cells in the same culture of the previous year, we noticed that the cells were significantly longer this year. This told us that the increased growth, health, and chain length was due to the culture undergoing sexual reproduction. Chain length for F-28 was numerous at 4-8 cells per chain while both the pipetted and poured culture was most numerous at 1-2 cells per chain. Cell length was about 57 m in length and was uniform over the three flasks. I used an epifluorescent microscope to count and measure the cells. Guidelines that I used: 1. Count at least 100 chains 2. Dividing cells count as one cell in the chain
DOI: 10.6084/m9.figshare.90235.v2
title: Research data services at White Rose Research Online

description: This study, inspired by Tony Hey’s “The Data Deluge”, was carried out to discover whether the Institutional Repository is a suitable body to manage curation of and access to the source data created at the institution. This study surveyed research scientists at the White Rose Universities to discover their practices of and attitudes to research data storage, sharing and publication. Key role players in the research data management process were interviewed to investigate possible options for a data infrastructure, the capabilities of WRRO, the establishment of a discipline-based repository and issues of metadata assignment.
DOI: 10.6084/m9.figshare.90210
title: Cell concentration and fluorescence

description: These data represent a compilation of microscopic cell counts and the corresponding in vivo fluorescence. The cells in question are mostly planktonic diatoms with one dinoflagellate. The samples were collected in the context of oyster (Crassostrea virginica) grazing experiments described in Thessen, A.E., Q. Dortch, T.M. Soniat and G.J. Doucette (2009) Crassostrea virginica grazing on toxic and non-toxic diatoms. Toxicon.doi:10.1016/j.toxicon.2009.10.011. The Pseudo-nitzschia multiseries correlation is particularly bad because of a fungal infection in the culture.
DOI: 10.6084/m9.figshare.90211
title: Cell concentration and fluorescence

description: These are the raw data used to create the figures with the same title. They represent a compilation of microscopic cell counts and the corresponding in vivo fluorescence. The cells in question are mostly planktonic diatoms with one dinoflagellate. The samples were collected in the context of oyster (Crassostrea virginica) grazing experiments described in Thessen, A.E., Q. Dortch, T.M. Soniat and G.J. Doucette (2009) Crassostrea virginica grazing on toxic and non-toxic diatoms. Toxicon.doi:10.1016/j.toxicon.2009.10.011. The Pseudo-nitzschia multiseries correlation is particularly bad because of a fungal infection in the culture.
DOI: 10.6084/m9.figshare.90212
title: Does extra CO2 improve phytoplankton growth in culture?

description: We noticed that the Pseudo-nitzschia delicatissima (strain LaPn-4) cultures were growing better than expected. We speculated that the culture’s growth suddenly improved because it was getting more CO2 than before. We reached this conclusion because: 1. The culture grew better as flasks were changed more frequently 2. The culture grew better as the flasks we kept them in increased in volume 3. The culture was in flasks and had to be poured to take fluorometer readings and to do dilutions To investigate this, we used three 100mL cultures in 250mL Erlenmeyer flasks. F-28 was aerated using a pasteur pipette attached with rubber tubing and airline hose to an aquarium pump. The volumes needed for measurements and dilutions were removed and added using a sterile pipette. F-27 was not aerated. In order to take measurements and dilute the appropriate volume was pipetted in and out of the flask. F-26 was not aerated either. In order to obtain culture for measurements and dilutions the appropriate volume was poured into and out of the flask. No pipettes were used. All flasks were shaken to suspend cells evenly before fluorescence measurements were taken. These flasks had to be diluted often both before and after these trials began. As a result, obtaining three points for calculating a growth rate was difficult. We calculated three different growth rates for each flask and took averages. Later, upon comparing the length of the cells in the same culture of the previous year, we noticed that the cells were significantly longer this year. This told us that the increased growth, health, and chain length was due to the culture undergoing sexual reproduction. The data we have shows that the aerated culture had the best average growth rate followed by the pipetted culture and finally the pour culture.