This dataset is about books. It has 9 rows and is filtered where the book publisher is University of Texas Press for the Institute of Latin American Studies. It features 7 columns including author, publication date, language, and book publisher.

The Utah Geospatial Resource Center (UGRC) services are the authoritative source for Utah cadastral data used by the BLM Utah State Office. This includes the statewide Public Land Survey System (PLSS) and the Geographic Coordinate System Database (GCDB).The GCDB dataset provides the BLM and the public with a set of geographic foundation data that accurately depicts the locations of PLSS corners. The GCDB is based on the best and most current survey records available, and uses known geographic positions of control stations within the PLSS network. The GCDB is the key component of all cadastral information.All users of PLSS datasets ought to be aware that UGRC is continually updating these data. Updates are expected annually as horizontal control positions from published sources and global positioning system (GPS) observations are added. The GCDB grid is adjusted using various methods to determine the best geographic positions of the survey points.Links to UGRC Datasets:Utah PLSS Townships GCDB - https://opendata.gis.utah.gov/datasets/utah::utah-plss-townships-gcdb/about ;Utah PLSS Sections GCDB - https://opendata.gis.utah.gov/datasets/utah::utah-plss-sections-gcdb/about ;Utah PLSS Quarter Sections GCDB - https://opendata.gis.utah.gov/datasets/utah::utah-plss-quarter-sections-gcdb/about ;Utah PLSS Quarter Quarter Sections GCDB - https://opendata.gis.utah.gov/datasets/utah::utah-plss-quarter-quarter-sections-gcdb/about ;Utah PLSS Point GCDB - https://opendata.gis.utah.gov/datasets/utah::utah-plss-point-gcdb/about ;BLM Point of Contact:Calvert Norton Land Surveyor/PLSS Dataset ManagerBureau of Land Management, Utah State Office 440 W. 200 S., Suite 500 Salt Lake City, UT 84101 Phone: 801-539-4140 Email: cnorton@blm.gov

The CADNSDI or the Cadastral Publication Data Standard is the cadastral data component of the NSDI. This is the publication guideline for cadastral data that is intended to provide a common format and structure and content for cadastral information that can be made available across jurisdictional boundaries, providing a consistent and uniform cadastral data to meet business need that includes connections to the source information from the data stewards. The data stewards determine which data are published and should be contacted for any questions on data content or for additional information. The cadastral publication data is data provided by cadastral data producers in a standard form on a regular basis. Cadastral publication data has two primary components, land parcel data and cadastral reference data. It is important to recognize that the publication data are not the same as the operation and maintenance or production data. The production data is structured to optimize maintenance processes, is integrated with internal agency operations and contains much more detail than the publication data. The publication data is a subset of the more complete production data and is reformatted to meet a national standard so data can be integrated across jurisdictional boundaries and be presented in a consistent and standard form nationally.

PLSSQuarterQuarterSections_GCDB is the fourth level of a hierarchical break down of the Public Land Survey System Rectangular surveys. This data is CadNSDI Version 2.0 2015 of the Utah GCDB. This data set represents the GIS Version of the Public Land Survey System. Updates are expected annually as horizontal control positions from published sources and global positioning system (GPS) observations are added. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. This data was orginally published on 5/1/2015.The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division that has been defined for the first division. In most cases the smallest division for the cadastral reference will be the sixteenth but in some cases sections have only been divided to the quarter. Divisions below the sixteenth may be included in this feature class, but in most implementations these smaller divisions will be parcels.

This dataset is about books. It has 1 row and is filtered where the book is A mission for development : Utah universities and the Point Four Program in Iran. It features 7 columns including author, publication date, language, and book publisher.

This data set was created to depict right-of-way management allocations from the BLM Greater Sage-Grouse Land Use Planning Strategy in the Utah Sub-Region. This data was developed to reflect the right-of-way management allocations of the final agency decision to amend 14 BLM land use plans throughout the State of Utah. This planning process was initiated through issuance of a Notice of Intent published on December 6, 2011. This dataset is associated with the Record of Decision and Approved Resource Management Plan Amendments for the Great Basin Region, released to the public via a Notice of Availability on September 24, 2015. The purpose of the planning process was to address protection of greater sage-grouse, in partial response to a March 2010 decision by the U.S. Fish and Wildlife Service (FWS) that found the greater sage-grouse was eligible for listing under the authorities of the Endangered Species Act. The planning process resulted in preparation of a draft environmental impact statement (DEIS) and final environmental impact statement (FEIS) in close coordination with cooperating agencies for the planning effort. The planning effort addressed the adequacy of regulatory mechanisms found in the land use plans, as well as addressing the myriad threats to grouse and their habitat that were identified by the FWS. Data show areas where new ROWs will be avoided (with specific avoidance criteria and minimization measures identified in the Approved Plan Amendments), excluded from any rights-of-way, or open for consideration of new rights-of-way, consistent with other RMP management actions.

PLSSQuarterSections_GCDB is the third level of a hierarchical breakdown of the Public Land Survey System Rectangular surveys. This data is Version 2.3 2020 of the Utah PLSS Fabric. This data set represents the GIS Version of the Public Land Survey System. Updates are expected annually as horizontal control positions from published sources and global positioning system (GPS) observations are added. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. This data was originally published on 1/3/2017. This is no longer a standard and is now published as a Reference layer. This data is derived from the Second Division of the PLSS which includes quarter, quarter-quarter, sixteenth or government lot division of the PLSS.Updates were made to Quarter Sections in Utah County to add quarter sections to areas that were not broken down less than the Section level. They were added using information from points collected by county surveyors, that is in the data and extrapolating information from adjoining sections wherever possible. They are still areas that could not be interpreted well enough and they were left empty, beyond the section level.Quarter Sections were consolidated from the Quarter Quarter Sections to better represent the four quarters in all Aliquot Part areas. Areas with Lots or Special Surveys remain as is. Updated 4/8/2022

Histology images from uniform tumor regions in TCGA Whole Slide Images (TCGA-UT-Internal, TCGA-UT-External)

This repository provides a benchmarking framework for the TCGA histology image dataset originally published on Zenodo. It includes predefined train/validation/test splits and example code for foundation model evaluation.

  Task

Classification of 31 different cancer types from tumor histopathological images.

  Original Dataset Description

This… See the full description on the dataset page: https://huggingface.co/datasets/dakomura/tcga-ut.

This data set was created to depict off-highway area designations from the BLM Greater Sage-Grouse Land Use Planning Strategy in the Utah Sub-Region. This data was developed to reflect the off-highway area allocations contained in the final agency decision to amend 14 BLM land use plans throughout the State of Utah. This planning process was initiated through issuance of a Notice of Intent published on December 6, 2011. This dataset is associated with the Record of Decision and Approved Resource Management Plan Amendments for the Great Basin Region, released to the public via a Notice of Availability on September 24, 2015. The purpose of the planning process was to address protection of greater sage-grouse, in partial response to a March 2010 decision by the U.S. Fish and Wildlife Service (FWS) that found the greater sage-grouse was eligible for listing under the authorities of the Endangered Species Act. The planning process resulted in preparation of a draft environmental impact statement (DEIS) and final environmental impact statement (FEIS) in close coordination with cooperating agencies for the planning effort. The planning effort addressed the adequacy of regulatory mechanisms found in the land use plans, as well as addressing the myriad threats to grouse and their habitat that were identified by the FWS. Data identify areas as "open" for cross-country driving, "limited to designated routes" where use is allowed on routes that have been designated as part of a formal transportation planning process, "limited to existing routes" where use is allowed on routes that exist on the landscape, and "closed" where OHV use is not allowed.

The top of the Upper Cretaceous Dakota Sandstone is present in the subsurface throughout the Uinta and Piceance basins of UT and CO and is easily recognized in the subsurface from geophysical well logs. This digital data release captures in digital form the results of two previously published contoured subsurface maps that were constructed on the top of Dakota Sandstone datum; one of the studies also included a map constructed on the top of the overlying Mancos Shale. A structure contour map of the top of the Dakota Sandstone was constructed as part of a U.S. Geological Survey Petroleum Systems and Geologic Assessment of Oil and Gas in the Uinta-Piceance Province, Utah and Colorado (Roberts, 2003). This surface, constructed using data from oil and gas wells, from digital geologic maps of Utah and Colorado, and from thicknesses of overlying stratigraphic units, depicts the overall configuration of major structural trends of the present-day Uinta and Piceance basins and was used to ...

This data set was created to depict mineral material management allocations from the BLM Greater Sage-Grouse Land Use Planning Strategy in the Utah Sub-Region. This data was developed to reflect mineral material allocations from MA-MR-13 and MA-MR-14 from the final agency decision to amend 14 BLM land use plans throughout the State of Utah. This planning process was initiated through issuance of a Notice of Intent published on December 6, 2011. This dataset is associated with the Record of Decision and Approved Resource Management Plan Amendments for the Great Basin Region, released to the public via a Notice of Availability on September 24, 2015. The purpose of the planning process was to address protection of greater sage-grouse, in partial response to a March 2010 decision by the U.S. Fish and Wildlife Service (FWS) that found the greater sage-grouse was eligible for listing under the authorities of the Endangered Species Act. The planning process resulted in preparation of a draft environmental impact statement (DEIS) and final environmental impact statement (FEIS) in close coordination with cooperating agencies for the planning effort. The planning effort addressed the adequacy of regulatory mechanisms found in the land use plans, as well as addressing the myriad threats to grouse and their habitat that were identified by the FWS. The Approved Plan Amendments note that, while new mineral material sites are closed in greater sage-grouse Priority Habitat Management Areas, existing sites can expand and new free-use sites can be developed so long as they meet various identified minimization actions.

This dataset is about books. It has 273 rows and is filtered where the book publisher is Utah State University Press. It features 5 columns: author, publication date, book publisher, and BNB id.

The following datasets and tables correspond to the data elements reported in the annual Public Library Service – PLS (formerly the Federal State Cooperative System [FSCS] for Public Library Data) survey published by the Institute of Museum and Library Services (IMLS). These data elements are a sub-set of the “Statistical Annual Report of Public Library Services” survey administered by the Utah State Library Division.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

The layers within this feature service represent the spatial extent and boundaries of the Surface Management Agency (SMA), which generally defines when the land is either: Withdrawn by some administrative or legislative action, acquired, or exchanged among government agencies. The Utah School and Institutional Trust Lands Administration (SITLA) holds responsibility maintaining land status for Utah and depicts this at the 1:24,000 scale. This information is published monthly by BLM to reflect changes in trust lands, other state land and private Land. While this dataset illustrates various government agency surface management areas and quantifies geographic acreage, these are computed by mathematical formulas. They are not derived from legal documents or associated with title documents or survey records. Data within these services are a live copy of BLM Utah's enterprise production environment. Quality control is conducted annually.Complete metadata for these data sets can be found at:BLM UT Surface Management Agency (Polygon)

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 University of Texas Post-Fay lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

Reference Posts are signs located in physical locations. They stay in roughly the same place over time and do not change when other sections of the road are realigned. This layer also contains current ALRS linear measures (LM) for the sign feature.This is a Roads and Highways Event Layer - RP StationingFor more information on the difference between reference post locations along the roadway and the ALRS mileage, please refer to the Linear Measure vs Sign Location informational page

With the help of local and regional natural resource professionals, we developed a broad-scale, spatially-explicit assessment of 146 miles (~20,000 acres) of the Colorado River mainstem in Grand and San Juan Counties, Utah that can be used to support conservation planning and riparian restoration prioritization. For the assessment we: 1) acquired, modified or created spatial datasets of Colorado River bottomland conditions; 2) synthesized those datasets into habitat suitability models and estimates of natural recovery potential, fire risk and relative cost; 3) investigated and described dominant ecosystem trends and human uses, and; 4) suggested site selection and prioritization approaches. Here, we make available to the public spatial data associated with this work. The data include 51 shape files: 6 of these are related to fluvial geomorphology and hydrology; 1 contains riparian vegetation and surrounding land cover types; 30 are related to habitat or conservation element models (including model components and model results); and 14 are related to supplemental models including the relative cost of restoration, site recovery potential, and fire models. The data released here are associated with a publication that describes the project and results in more detail: Rasmussen, C.G., and P.B. Shafroth. 2016. Conservation planning for the Colorado River in Utah. Colorado Mesa University, Ruth Powell Hutchins Water Center, Scientific and Technical Report No. 3. 93p.

The Digital Geologic-GIS Map of the Hatch Trading Post Quadrangle, Utah is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (hatp_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (hatp_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (hatp_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (hove_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (hove_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (hatp_geology_metadata_faq.pdf). Please read the hove_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: National Park Service Geologic Resources Inventory and U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (hatp_geology_metadata.txt or hatp_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:250,000 and United States National Map Accuracy Standards features are within (horizontally) 127 meters or 416.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This dataset was created to facilitate the BLM Greater Sage-Grouse Land Use Planning Strategy in the Utah Sub-Region. This data was developed and addressed, and used during preparation of a draft and final environmental impact statement and the record of decision to amend 14 BLM land use plans throughout the State of Utah. This planning process was initiated through issuance of a Notice of Intent published on December 6, 2011. This dataset is associated with the Record of Decision and Approved Resource Management Plan Amendments for the Great Basin Region, released to the public via a Notice of Availability on September 24, 2015. The purpose of the planning process was to address protection of greater sage-grouse, in partial response to a March 2010 decision by the U.S. Fish and Wildlife Service (FWS) that found the greater sage-grouse was eligible for listing under the authorities of the Endangered Species Act. The planning process resulted in preparation of a draft environmental impact statement (DEIS) and final environmental impact statement (FEIS) in close coordination with cooperating agencies for the planning effort. The planning effort addressed the adequacy of regulatory mechanisms found in the land use plans, as well as addressing the myriad threats to grouse and their habitat that were identified by the FWS. This polygon is largely based on the existing land use plan boundaries which had a Record of Decision as of the initiation of the amendment process.

This dataset includes results and reports from the injection/production test for wells 16A(78)-32 and 16B(78)-32 in August, 2024 at Utah FORGE. Materials include injection, post stimulation production, flow rate, gamma, temperature and pressure survey results. For the respective wells, injection and production profile results and interpretations are provided in .xlsx and .las file formats. Additionally, for both wells, preliminary and final reports are included and provide logging procedures and visualizations of the results.

Introduction

Magnetic Resonance Imaging (MRI) is widely recommended as a primary non-invasive diagnostic tool for endometriosis. Endometriomas affect 17–44% of women diagnosed with the condition. Accurate MRI-based ovary segmentation in endometriosis patients is essential for detecting endometriomas, guiding surgery, and predicting post-operative complications. However, ovary segmentation becomes challenging when the ovary is deformed or absent, often due to surgical resection, emphasizing the need for highly experienced clinicians. An automatic segmentation pipeline for pelvic MRI in endometriosis patients could greatly reduce the manual workload for clinicians and help standardize ovary segmentation.

The UTHealth Endometriosis MRI Dataset (UT-EndoMRI) includes multi-sequence MRI scans and structural labels collected from two clinical institutions, Memorial Hermann Hospital System and Texas Children’s Hospital Pavilion for Women. The first dataset comprises MRI scans and labels from 51 patients collected before 2022, featuring T2-weighted and T1-weighted fat-suppressed MRI sequences. The uterus, ovaries, endometriomas, cysts, and cul-de-sac structures were manually segmented by three raters. The second dataset, collected in 2022, consists of MRI scans and labels from 82 endometriosis patients. These sequences include T1-weighted, T1-weighted fat suppression, T2-weighted, and T2-weighted fat suppression MRI. In this dataset, the uterus, ovaries, and endometriomas were manually contoured by a single rater. Using these datasets, we investigated interrater agreement and developed an automatic ovary segmentation pipeline, RAovSeg, for endometriosis.

The study and the data sharing were approved by the Committee for the Protection of Human Subjects at UTHealth (protocol no. HSC-SBMI-22-0184). The UT-EndoMRI dataset is available for free use exclusively in non-commercial scientific research.

Endometriosis MRI

This dataset includes MRI scans and labels from two clinical institutions. The data from the first institution can be found in the ```D1_MHS/ ```directory, while the data from the second institution are located in the ```D2_TCPW/``` directory. Each subfolder contains MRI scans and corresponding labels from different raters.

The naming conventions for the files are as follows:

MRI scans:
D[dataset ID]- [patient ID] _ [MRI sequence].nii.gz

Anatomical structure labels:
D[dataset ID]- [patient ID] _ [structure name] _ r[rater ID].nii.gz

For the labels in the ```D2_TCPW/ ```directory, since they were generated by a single rater, there is no rater ID included in the file names.

The abbreviations used for naming:
T1: T1-weighted MRI
T1FS: T1-weighted fat suppression MRI
T2: T2-weighted MRI
T2FS: T2-weighted fat suppression MRI
ov: ovary
ut: uterus
em: endometrioma
cy: cyst
cds: cul de sac

For example, the file located at ```UT-EndoMRI/D1_MHS/D1-000/D1-000_T1FS.nii.gz```represents the T1-weighted fat suppression MRI for subject 000 in dataset 1. The file at ```UT-EndoMRI/D1_MHS/D1-000/D1-000_ ut_r1.nii.gz``` is the uterus segmentation manually contoured by rater 1 for subject 000 in dataset 1. The file at```UT-EndoMRI/ D2_TCPW/D2-006/D2-006_ cy.nii.gz``` is the cyst segmentation manually contoured for subject 006 in dataset 2.

MRI sequences may be missing due to a lack of acquisition.

The MR Scanner information for Dataset 1 is available in 'SiteScannerInfo.csv'.

Train/Validation/Test Replication

The data split for RAovSeg training, validation, and testing is provided as follows:
- Training/validation subjects IDs: D2-000 – D2-007
- Testing subjects IDs: D2-008 – D2-037
All data in dataset 1, as well as other data in dataset 2, are not used in RAovSeg development.

Data Acquisition

This dataset was acquired at the Texas Medical Center, within the Memorial Hermann Hospital System and the Texas Children’s Hospital Pavilion for Women. The study and the data sharing were approved by the Committee for the Protection of Human Subjects at UTHealth (protocol no. HSC-SBMI-22-0184).

User Agreement

The UT-EndoMRI dataset is available for free use exclusively in non-commercial scientific research. Any publications resulting from its use must cite the following paper.

X. Liang, L.A. Alpuing Radilla, K. Khalaj, H. Dawoodally, C. Mokashi, X. Guan, K.E. Roberts, S.A. Sheth, V.S. Tammisetti, L. Giancardo. "A Multi-Modal Pelvic MRI Dataset for Deep Learning-Based Pelvic Organ Segmentation in Endometriosis." (submitted)

Funding

This work has been supported by the Robert and Janice McNair Foundation.

Research Team

Here are the people behind this data acquisition effort:
Xiaomin Liang, Linda A Alpuing Radilla, Kamand Khalaj, Haaniya Dawoodally, Chinmay Mokashi, Xiaoming Guan, Kirk E Roberts, Sunil A Sheth, Varaha S Tammisetti, Luca Giancardo

Acknowledgements

We would also like to acknowledge for their support: Memorial Hermann Hospital System and Texas Children’s Hospital Pavilion for Women.