cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4225/08/55dffc6c56916
title: Maps of iron oxides and the color of Australian soil

description: Iron (Fe) oxide mineralogy in most Australian soils is poorly characterized, even though Fe oxides play an important role in soil function. Fe oxides reflect the conditions of pH, redox potential, moisture, and temperature in the soil environment. The strong pigmenting effect of Fe oxides gives most soils their color, which is largely a reflection of the soil’s Fe mineralogy. Visible-near-infrared (vis-NIR) spectroscopy can be used to identify and measure the abundance of certain Fe oxides in soil, and the visible range can be used to derive tristimuli soil color information. We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer with a wavelength range of 350-2500 nm. We determined the Fe oxide abundance for each sample using the diagnostic absorption features of hematite (near 880 nm) and goethite (near 920 nm) and derived a normalized iron oxide difference index (NIODI) to better discriminate between them. The NIODI was generalized across Australia with its spatial uncertainty using sequential indicator simulation, which resulted in a map of the probability of the occurrence of hematite and goethite. We also derived soil RGB color from the spectra and mapped its distribution and uncertainty across the country using sequential Gaussian simulations. The simulated RGB color values were made into a composite true color image and were also converted to Munsell hue, value, and chroma. These color maps were compared to the map of the NIODI, and both were used to interpret our results. The maps were validated by randomly splitting the data into training and test data sets, as well as by comparing our results to existing studies on the distribution of Fe oxides in Australian soils.
Attributes: 
Units of measurement: 
1.	Munsell Hue; 
2.	Munsell Chroma; 
3.	Munsell value; 
4.	NIODI; 
5.	NIODI uncertainty.
For details please see Viscarra Rossel et al. (2010). 

Data Type: Float Grid. 

Map projection: Lambert Conformal Conic. 

Datum: GDA94. 

Map units: Decimal degrees. 

Resolution: 10,000 metres. 

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DOI: 10.6073/pasta/08a41306d9b231fa46a5923b46aa0419
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 2008-03-03
DOI: 10.6073/pasta/66a0f6c21109d16d0e6b2252388ce613
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 1998-01-19
DOI: 10.6073/pasta/d13b3b91fa10201ce703db8e85631f77
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 2008-03-19
DOI: 10.14457/ru.the.2003.77
title: ชีวิตไร้ตัวตนของกะเทยเปลี่ยนเพศ /
DOI: 10.14457/ru.the.2003.78
title: ความร่วมมือระหว่างประเทศ เพื่อการพัฒนาศักยภาพแรงงานสตรีในประเทศไทย /
DOI: 10.14457/ru.the.2003.79
title: ผลของการฝึกพฤติกรรมกล้าแสดงออก ที่มีต่อความวิตกกังวลในการพูดในที่ชุมชน ของนักศึกษาวิทยาลัยพณิชยการเชตุพน กรุงเทพฯ /
DOI: 10.14457/ru.the.2003.80
title: การประเมินหลักสูตรโครงการบริหารธุรกิจมหาบัณฑิต สำหรับผู้จัดการยุคใหม่ คณะบริหารธุรกิจ มหาวิทยาลัยรามคำแหง /
DOI: 10.15468/0ljpzp
title: Specimen/Occurrence records from the Scratchpad "Amaryllidaceae"
DOI: 10.15468/draulq
title: Specimen/Occurrence records from the Scratchpad "Systematics and taxonomy in scuttle flies"
DOI: 10.15468/go3eqb
title: Specimen/Occurrence records from the Scratchpad "Neogene Bryozoa of Britain"
DOI: 10.15468/kedl2l
title: Specimen/Occurrence records from the Scratchpad "London Fungi Recording"
DOI: 10.15468/nlffwi
title: Specimen/Occurrence records from the Scratchpad "Acanthocephala"
DOI: 10.15468/te5ows
title: Specimen/Occurrence records from the Scratchpad "Platypezidae - The Flat-footed Flies"
DOI: 10.15468/vna5is
title: Specimen/Occurrence records from the Scratchpad "Marine Mollusca of New Zealand"
DOI: 10.3886/e30744v2
title: Smarr student sleep timing logs

description: Stability of sleep and circadian rhythms are important for healthy learning and memory. While experimental manipulation of lifestyle and learning outcomes present major obstacles, the ongoing increase in data sources allows retrospective data mining of people’s sleep timing variation. Here I use digital sleep-log data generated by 1109 students in a biology lab course at the University of Washington to test the hypothesis that higher variance in time asleep and later sleep onset times negatively correlate with class performance, used here as a real-world proxy for learning and memory. I find that sleep duration variance and mean sleep onset times both significantly correlate with class performance. These correlations are strong on weeknights, but disappear on Friday and Saturday nights (“free nights”). These correlations also show large sex differences, with women showing substantially stronger (both larger and more powerful) negative correlations than men. Finally, though these data come with no demographic information beyond sex, the constructed demographic groups of “larks” and “owls” within the sexes reveal a significant decrease in performance of owls relative to larks in male students, whereas for the correlation of performance with sleep-onset time for all male students was only a near-significant trend. This provides a proof of concept that deeper demographic mining of digital logs in the future may identify subgroups for which certain sleep phenotypes have greater predictive value for performance outcomes. The data analyzed are validated by showing known patterns, including sleep-timing delays from weeknights to free-nights, and sleep-timing delays in men relative to women. These findings support the hypothesis that modern schedule impositions on sleep and circadian timing have consequences for real-world learning and memory. This study also highlights the low-cost, large-scale benefits of personal, daily, digital records as an augmentation of sleep and circadian studies.
<br>This work was unfunded.
<br>
<br>
DOI: 10.3886/e30753v4
title: Smarr student sleep timing logs

description: Stability of sleep and circadian rhythms are important for healthy learning and memory. While experimental manipulation of lifestyle and learning outcomes present major obstacles, the ongoing increase in data sources allows retrospective data mining of people’s sleep timing variation. Here I use digital sleep-log data generated by 1109 students in a biology lab course at the University of Washington to test the hypothesis that higher variance in time asleep and later sleep onset times negatively correlate with class performance, used here as a real-world proxy for learning and memory. I find that sleep duration variance and mean sleep onset times both significantly correlate with class performance. These correlations are strong on weeknights, but disappear on Friday and Saturday nights (“free nights”). These correlations also show large sex differences, with women showing substantially stronger (both larger and more powerful) negative correlations than men. Finally, though these data come with no demographic information beyond sex, the constructed demographic groups of “larks” and “owls” within the sexes reveal a significant decrease in performance of owls relative to larks in male students, whereas for the correlation of performance with sleep-onset time for all male students was only a near-significant trend. This provides a proof of concept that deeper demographic mining of digital logs in the future may identify subgroups for which certain sleep phenotypes have greater predictive value for performance outcomes. The data analyzed are validated by showing known patterns, including sleep-timing delays from weeknights to free-nights, and sleep-timing delays in men relative to women. These findings support the hypothesis that modern schedule impositions on sleep and circadian timing have consequences for real-world learning and memory. This study also highlights the low-cost, large-scale benefits of personal, daily, digital records as an augmentation of sleep and circadian studies.
<br>This work was unfunded.
<br>
<br>
DOI: 10.3886/e31607v2
title: Maternal Anxiety: Does It Affect Foetal Growth

description: On 2016-08-20, the openICPSR web site was moved to new software. In the migration process, some projects were not published in the new system because the decisions made in the old site did not map easily to the new setup. An ICPSR staff member manually published these projects, taking care to preserve the original wishes of the depositor.
DOI: 10.3886/e31619v3
title: Maternal Anxiety: Does It Affect Foetal Growth

description: On 2016-08-20, the openICPSR web site was moved to new software. In the migration process, some projects were not published in the new system because the decisions made in the old site did not map easily to the new setup. An ICPSR staff member manually published these projects, taking care to preserve the original wishes of the depositor.
DOI: 10.3886/e44849v4
title: Charter School Vote in Georgia

description: No summary available for this study.
DOI: 10.4225/08/55dffca4715d8
title: Maps of clay minerals - kaolinite, illite and smectite in Australian soils

description: Clay minerals are the most reactive inorganic components of soils. They help to determine soil properties and largely govern their behaviors and functions. Clay minerals also play important roles in biogeochemical cycling and interact with the environment to affect geomorphic processes such as weathering, erosion and deposition. This data provides new spatially explicit clay mineralogy information for Australia that will help to improve our understanding of soils and their role in the functioning of landscapes and ecosystems. I measured the abundances of kaolinite, illite and smectite in Australian soils using near infrared (NIR) spectroscopy. Using a model-tree algorithm, I built rule-based models for each mineral at two depths (0-20 cm, 60-80 cm) as a function of predictors that represent the soil-forming factors (climate, parent material, relief, vegetation and time), their processes and the scales at which they vary. The results show that climate, parent material and soil type exert the largest influence on the abundance and spatial distribution of the clay minerals; relief and vegetation have more local effects. I digitally mapped each mineral on a 3 arc-second grid. The maps show the relative abundances and distributions of kaolinite, illite and smectite in Australian soils. Kaolinite occurs in a range of climates but dominates in deeply weathered soils, in soils of higher landscapes and in regions with more rain. Illite is present in varied landscapes and may be representative of colder, more arid climates, but may also be present in warmer and wetter soil environments. Smectite is often an authigenic mineral, formed from the weathering of basalt, but it also occurs on sediments and calcareous substrates. It occurs predominantly in drier climates and in landscapes with low relief. These new clay mineral maps fill a significant gap in the availability of soil mineralogical information. They provide data to for example, assist with research into soil fertility and food production, carbon sequestration, land degradation, dust and climate modeling and paleoclimatic change.

Attributes: 
Units of measurement: 
1.	Abundance of kaolin (0 - 1) for the 0-20 cm  and 60-80 cm depths; 
2.	Abundance of illite (0 - 1) for the 0-20 cm  and 60-80 cm depths; 
3.	Abundance of smectite (0 - 1) for the 0-20 cm  and 60-80 cm depths; 
4.	Ternary RGB  image of mineral composition for the 0-20 cm  and 60-80 cm depths. 

For details please see Viscarra Rossel (2011).

Data Type: Float Grid. 
Kaolinite, illite, smectite composite maps in GEOTIFF format. 

Map projections: Geographic. 

Datum: GDA94 

Map units: Decimal degrees. 

Resolution: 0.00083333333 degrees. 

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DOI: 10.4225/08/55dffca48f284
title: Maps of Australian soil composition measured with visible-near infrared spectra

description: We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer. These spectra provide an integrative measure that provides information on the fundamental characteristics and composition of the soil, including colour, iron oxide, clay and carbonate mineralogy, organic matter content and composition, the amount of water present and particle size. This soil information content of the spectra was summarised using a principal component analysis (PCA). We used model trees to derive statistical relationships between the scores of the PCA and 31 predictors that were readily available and we thought might best represent the factors of soil formation (climate, organisms, relief, parent material, time and the soil itself). The models were validated and subsequently used to produce digital maps of the information content of the spectra, as summarised by the PCA, with estimates of  prediction error at 3-arc seconds (around 90 m) pixel resolution. The maps might be useful in situations requiring high-resolution, quantitative soil information e.g. in agricultural, environmental and ecologic modelling and for soil mapping and classification.

Attributes: 
Units of measurement: 
1.	Principal component 1; 
2.	Principal component 3; 
3.	Principal component 3. 

For interpretations please see Viscarra Rossel & Chen (2011). 

Data Type: Float Grid. 

Map Projection: Geographic. 

Datum: GDA94. 

Map units: Decimal degrees. 

Resolution: 0.00083333333 degrees. 

File Header Information:
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nrows         40373; 
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DOI: 10.6073/pasta/664670b4ee6536bc214f7245472d7598
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 2008-04-04
DOI: 10.14457/ru.res.2002.1
title: พัฒนาการสำนักหอสมุดกลาง มหาวิทยาลัยรามคำแหง /
DOI: 10.14457/ru.res.2002.2
title: การศึกษาความสัมพันธ์ระหว่างปัจจัยบางประการ กับการตัดสินใจเลือกอาชีพ ของนักเรียนมัธยมศึกษาตอนปลาย โรงเรียนสาธิตมหาวิทยาลัยรามคำแหง /
DOI: 10.14457/ru.res.2002.3
title: การใช้ทรัพยากรสารสนเทศของนักศึกษาปริญญาโท มหาวิทยาลัยรามคำแหง สาขาวิทยบริการเฉลิมพระเกียรติ /
DOI: 10.14457/ru.res.2003.1
title: การวิเคราะห์บทบรรณาธิการ ของหนังสือพิมพ์แนวเศรษฐกิจ /
DOI: 10.14457/ru.res.2003.2
title: ความต้องการใช้สารนิเทศของนักศึกษาระดับบัณฑิตศึกษาในสำนักหอสมุดกลาง มหาวิทยาลัยรามคำแหง /
DOI: 10.14457/ru.res.2003.3
title: การปกครองและการพัฒนาในแอฟริกา /
DOI: 10.14457/ru.res.2003.5
title: ประสิทธิภาพการปฏิบัติงานของงานบัญชี กองคลัง สำนักงานอธิการบดี มหาวิทยาลัยรามคำแหง /
DOI: 10.14457/ru.the.2003.81
title: การศึกษาปัจจัยที่มีความสัมพันธ์กับความสนใจในการประกอบอาชีพอิสระ ของประชาชนในจังหวัดนนทบุรี /
DOI: 10.15468/mxftou
title: Specimen/Occurrence records from the Scratchpad "Pacific Islands Lepidoptera"
DOI: 10.15468/nyjfhf
title: Specimen/Occurrence records from the Scratchpad "lusoborboletas"
DOI: 10.15468/rmqjj4
title: Specimen/Occurrence records from the Scratchpad "invertebrate"
DOI: 10.15468/tyohdo
title: Specimen/Occurrence records from the Scratchpad "Páramo Flora"
DOI: 10.14457/ru.res.2003.4
title: การมีส่วนร่วมของพระสงฆ์ในการป้องกันการแพร่ระบาดของยาบ้าในประเทศไทย /
DOI: 10.14457/ru.res.2003.6
title: ศึกษาทัศนะของผู้บริหาร อาจารย์ และนักศึกษาที่มีต่อการจัดกิจกรรมนักศึกษา ในมหาวิทยาลัยรามคำแหง /
DOI: 10.14457/ru.res.2003.7
title: พฤติกรรมผู้บริโภคกับการบริหารจัดการด้านการตลาด สำนักงานตลาด กรุงเทพมหานคร /
DOI: 10.15468/5jzope
title: Specimen/Occurrence records from the Scratchpad "Myrtaceae of Chile "
DOI: 10.6073/pasta/90297be05b059ce6b54a66ecf504f6ad
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 2008-04-20
DOI: 10.15468/g0axhz
title: Specimen/Occurrence records from the Scratchpad "heteroptera"
DOI: 10.3886/e45052v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.3886/e45059v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.3886/e45086v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.3886/e45164v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.3886/e45190v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.6073/pasta/4b7de715ca446cdadfec6b3595c3a8ba
title: LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Santa Barbara Coastal LTER collected on 2008-05-22
DOI: 10.15468/cg5beo
title: Specimen/Occurrence records from the Scratchpad "Poaceae"
DOI: 10.15468/oxdx7k
title: Specimen/Occurrence records from the Scratchpad "Mimosology"
DOI: 10.15468/pyu4tx
title: Specimen/Occurrence records from the Scratchpad "Mormyridae - African weakly electric fishes"
DOI: 10.3886/e45068v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>
DOI: 10.3886/e45077v1
title: Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics [2014]

description: Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.
<br>
<br>