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Collection
Stanford Research Data
The benefits of protected areas depend on compliance, and achieving protection remains a challenge in intensely used areas where conservation and socioeconomic goals are in real or apparent conflict. One recent innovation – satellite tracking of commercial fishing vessels – has been introduced to help with ocean protection initiatives and build trust between fishers and managers. We paired vessel traffic data before and during a temporary closure in the Adriatic Sea with data on fish nursery habitat to examine changes in fishing effort and their potential consequences. Trawlers generally complied with the closure but maintained overall effort by trawling more intensely outside of the no-trawl zone, especially near its borders and closer to shore. We detected stronger than expected fishing effort in a sub-region within the protected area, suggesting that this location should be closely monitored for compliance. Notably, fishing effort was relocated to nursery grounds for some exploited species, illustrating the importance of understanding species’ life histories and habitat distribution in the design of protected areas.
Collection
Stanford Research Data
This data repository contains the raw PET data (Figure 5), onset arrival time (Figure 6), permeability inversion results (Figure 7), and trajectory data (Figure 8) for the paper titled 'Calculating trajectories associated with solute transport in a heterogeneous medium'. Matlab codes for data plotting may be made available upon request.
Database topics
Art, Architecture and Design
Dataset
Digital: Excel; csv.
Collection
Electronic Acquisitions
For each format (Excel and .csv) there are two files - one for the buildings (one row per building) and the other for the companies involved (one row per company per role per building). The two files are linked by the Emporis Building Number (EBN), the unique ID for each building record on Emporis database, which can be found in column A of both files.

4. Eviction Lab. [2018]

Database topics
Law; Statistical and Numeric Data
Dataset
1 online resource : color illustrations
"Drawing on tens of millions of records, the Eviction Lab at Princeton University has published the first ever dataset of evictions in America, going back to 2000. We hope you’ll join us in using the tools of this website to discover new facts about how eviction is shaping your community, raising awareness and working toward new solutions."--About page.
Collection
Stanford Research Data
The Fundamental Kinetic Database Utilizing Shock Tube Measurements Database summarizes the published shock tube experimental work performed under the supervision of Prof. Ronald K. Hanson of the Mechanical Engineering Department at Stanford University. The database covers the years from 1974 to 2013 inclusively. The database is divided into three types of data: ignition delay times, species time-history measurements, and reaction rate measurements. Volumes are in DOCX format and data tables in the volumes can be easily cut and pasted into separate user spread sheets. Volume 1 of the Fundamental Kinetic Database Utilizing Shock Tube Measurements includes a summary of the ignition delay time data measured and published by the Shock Tube Group in the Mechanical Engineering Department of Stanford University. The cut-off date for inclusion into this volume was January 2005. Volume 2 includes a summary of the species concentration time-histories. The cut-off date for inclusion in this volume was December 2005. Some of the figures embedded in this DOCX file can be opened using ORIGIN software. The data in this volume is available in tabular form in the accompanying ZIP file or in this volume. Volume 3 includes a summary of the reaction rate measurements. The cut-off date for inclusion in this volume was January 2009. Volume 4 includes a summary of the ignition delay time data. The start data for inclusion into this volume is January 2005 (the cutoff date for Volume 1) and the cutoff date is January 2014. Volume 5 includes a summary of the species concentration time-histories. The cut-off date for inclusion in this volume was January 2014. The format of this volume differs from that of Volume 2 in that we have not included the data files. Some of this data is available in the relevant papers and some of the data files may be accessible by contacting Dr. David Davidson at dfd@stanford.edu. Much of this data was used for reaction rate constant determinations and the mixtures in the experiments reflect this use; the mixtures were designed to isolate or enhance the sensitivity of the measured species to a particular reaction rate constant. Volume 6 includes a summary of the reaction rate measurements. The cut-off date for inclusion in this volume was January 2014.
Collection
Mapping the Republic of Letters
This dataset includes known, documented attendees of Julie de Lespinasse's salon in Paris from 1764 to 1776.
Collection
Marine Biogeochemistry Data
Output from global inverse model optimized to three different combinations of isotope effects for nitrate reduction (eNAR), nitrite oxidation (eNXR), and nitrite reduction (eNIR).
Collection
Stanford Research Data
This a snapshot of the NeuroVault.org database. It include all public collections of statistical maps deposited in NeuroVault as long as they were linked to an external publication. This snapshot is an attempt to improve chances of long term persistance of data deposited in NeuroVault.org.
Collection
Mapping the Republic of Letters
Data for Giacomo Casanova's network during his first two trips to Paris. The focus is on performers, intellectuals, and elite connections that the Venetian established in Paris to help with his social advancement.
Collection
Stanford Research Data
Linkages between climate and mental health are often theorized but remain poorly quantified. In particular, it is unknown whether suicide, a leading cause of death globally, is systematically affected by climatic conditions. Using multiple decades of comprehensive data from both the US and Mexico, we find that suicide rates rise 0.7% in US counties and 2.1% in Mexican municipalities for a 1C increase in monthly average temperature. This effect is similar in hotter versus cooler regions and has not diminished over time, indicating limited historical adaptation. Analysis of depressive language in >600 million social media updates further suggests that mental wellbeing deteriorates during warmer periods. We project that unmitigated climate change (RCP8.5) could result in a combined 9-40 thousand additional suicides (95% CI) across the US and Mexico by 2050, representing an change in suicide rates comparable to the estimated impact of economic recessions, suicide prevention programs, or gun restriction laws.
Collection
Stanford Research Data
Replication data for "Large potential reduction in economic damages under UN mitigation targets", Nature, 2018
Collection
Stanford Research Data
Decoys that were generated as part of the RNA-protein structure prediction benchmark in the citation below.

13. The Salons Project [2018] Online

Collection
Mapping the Republic of Letters
This dataset for The Salons Project includes metadata for known attendees of the salons of Graffigny, Tencin, Geoffrin, Deffand, Lespinasse, and Necker, as well as some data for other contemporaneous salons incidentally collected throughout the research process.

14. CMOS Technology Scaling Trend [2017] Online

Collection
Stanford Research Data
This data set is a compilation of the historical CMOS technology scaling data presented in the ITRS, journals, and conferences including IEDM and VLSI Technology from 1988 and onward. Chi-Shuen Lee, Jieying Luo, and H.-S. Philip Wong at Stanford University compiled the data; Thomas N. Theis at Columbia University provided the data originally compiled by Robert W. Keyes at IBM T.J. Watson Research Center and published in Figure 1 of Rolf Landauer's 1988 paper. The historical scaling trend of logic switching energy and integration density were published in Figure 1 and 2, respectively in the paper, "The End of Moore’s Law: A New Beginning for Information Technology" by Theis and Wong (see Related Published Work below for the full citation.
Collection
Stanford Research Data
In matrix recovery from random linear measurements, one is interested in recovering an unknown $M$-by-$N$ matrix $X_0$ from $n
Collection
Stanford Research Data
R code and processed input data files for manuscript results and graphics
Collection
Reproducible Research Support for Statistics of the Microbiome
Complete ribosomal sequence variant abundance data and analysis files for paper entitled: Multidomain Analyses of a Longitudinal Human Microbiome Intestinal Cleanout Perturbation Experiment. This work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods. Funded by NIH TR01 grant AI112401.
Collection
Payne Paleobiology Lab Data Files
Over the past 3.8 billion years, the maximum size of living organisms has increased by approximately 18 orders of magnitude. Much of this increase is associated with two major evolutionary innovations: the evolution of eukaryotes from prokaryotic cells ~ 1.9 billion years ago (Ga), and multicellular life diversifying from unicellular ancestors ~ 0.6 Ga. However, the quantitative relationship between organismal size and structural complexity remains poorly documented. We assessed this relationship using a comprehensive dataset that includes organismal size and level of biological complexity for 11,172 extant genera. We find that the distributions of sizes within complexity levels are unimodal whereas the aggregate distribution is multimodal. Moreover, both the mean size and the range of size occupied increases with each additional level of vertical complexity. Interestingly, the increase in size range is non-symmetric; the maximum organismal size increases more than the minimum. The majority of the observed increase in organismal size over the Geozoic is accounted for by two discrete jumps in complexity rather than evolutionary trends within levels of complexity. Our results provide quantitative support for an evolutionary expansion away from a minimal size constraint and suggest a fundamental rescaling of the constrains on maximal size as biological complexity increases.
Collection
Stanford Research Data
# Data for Waskom and Wagner (2017) PNAS This repository contains data related to the following paper: Waskom M.L., Wagner A.D. (2017). Distributed representation of context by intrinsic subnetworks in prefrontal cortex. Proceedings of the National Academy of the Sciences, USA. The paper is available on the PNAS website: http://www.pnas.org/cgi/doi/10.1073/pnas.1615269114 Code implementing the results in the paper is included here and is also available on github: https://github.com/WagnerLabPapers/Waskom_PNAS_2017 The datasets in this repository are organized in subdirectories as follows: ## Preprocessed data - roi_cache: Preprocessed/denoised time series data from the ROIs in the paper ## Analysis results - decoding_analysis: Decoding analyses and estimated context preferences - spatial_analysis: Spatial organization analyses - correlation_analysis: Spontaneous correlation analyses ## Supporting data - mesh: Computationally reconstructed cortex models - reg: Functional template and registration relating it to anatomical space ## Analysis code - code: A copy of the analysis code repository available on github ## License Copyright (c) 2017, Michael Waskom and Anthony Wagner Released under a CC-BY 4.0 License
Collection
Stanford University, Program in Science, Technology and Society, Honors Theses
This Excel Spreadsheet includes the data and calculations used in my thesis, titled, "Opening Up Open Access: Investigating Alternate Funding Models to Stimulate Open Access Publishing".