The Hero Slider Admin extension for CKAN offers a user-friendly way to display visually appealing slides on the homepage of a CKAN instance. It allows administrators to easily manage a carousel of images and associated content directly from the CKAN sysadmin panel, enhancing the visual appeal and information delivery of the front page. This extension provides a simple method to highlight important datasets, announcements, or organizational branding. Key Features: Centralized Management: Administrators can manage hero slider content directly from the CKAN sysadmin panel, providing a centralized and convenient interface. Homepage Integration: The extension allows seamless integration of the hero slider into the CKAN homepage via a simple snippet added to the appropriate template. Customizable Display: The hero slider is designed for visual presentation making it simple to customize the homepage view. Database Storage: The extension employs database tables to store the slider content, ensuring it persists and is readily available. Technical Integration: The Hero Slider Admin extension integrates into the CKAN interface by adding a module to the sysadmin panel and utilizes a snippet that must be included in the website template to inject the visual element to the page. Installation requires enabling the extension through the ckan.plugins setting in CKAN's configuration file and initializing the database tables using a specific command-line tool (either ckan or paster depending on the CKAN version). This addition allows for dynamic data presentation with minimal front-end development. Benefits & Impact: Using the Hero Slider Admin extension offers a simple and intuitive way to improve the homepage appearance of a CKAN instance. By presenting key information in a visually engaging format, it can attract user attention and improve the overall user experience. It empowers administrators to keep the homepage looking fresh and relevant without requiring advanced web development skills.

This dataset is comprised of a collection of example DMPs from a wide array of fields; obtained from a number of different sources outlined below. Data included/extracted from the examples include the discipline and field of study, author, institutional affiliation and funding information, location, date created, title, research and data-type, description of project, link to the DMP, and where possible external links to related publications or grant pages. This CSV document serves as the content for a McMaster Data Management Plan (DMP) Database as part of the Research Data Management (RDM) Services website, located at https://u.mcmaster.ca/dmps. Other universities and organizations are encouraged to link to the DMP Database or use this dataset as the content for their own DMP Database. This dataset will be updated regularly to include new additions and will be versioned as such. We are gathering submissions at https://u.mcmaster.ca/submit-a-dmp to continue to expand the collection.

The SSURGO database contains information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS (Natural Resources Conservation Service). The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. The maps outline areas called map units. The map units describe soils and other components that have unique properties, interpretations, and productivity. The information was collected at scales ranging from 1:12,000 to 1:63,360. More details were gathered at a scale of 1:12,000 than at a scale of 1:63,360. The mapping is intended for natural resource planning and management by landowners, townships, and counties. Some knowledge of soils data and map scale is necessary to avoid misunderstandings. The maps are linked in the database to information about the component soils and their properties for each map unit. Each map unit may contain one to three major components and some minor components. The map units are typically named for the major components. Examples of information available from the database include available water capacity, soil reaction, electrical conductivity, and frequency of flooding; yields for cropland, woodland, rangeland, and pastureland; and limitations affecting recreational development, building site development, and other engineering uses. SSURGO datasets consist of map data, tabular data, and information about how the maps and tables were created. The extent of a SSURGO dataset is a soil survey area, which may consist of a single county, multiple counties, or parts of multiple counties. SSURGO map data can be viewed in the Web Soil Survey or downloaded in ESRI® Shapefile format. The coordinate systems are Geographic. Attribute data can be downloaded in text format that can be imported into a Microsoft® Access® database. A complete SSURGO dataset consists of:

GIS data (as ESRI® Shapefiles) attribute data (dbf files - a multitude of separate tables) database template (MS Access format - this helps with understanding the structure and linkages of the various tables) metadata

Resources in this dataset:Resource Title: SSURGO Metadata - Tables and Columns Report. File Name: SSURGO_Metadata_-_Tables_and_Columns.pdfResource Description: This report contains a complete listing of all columns in each database table. Please see SSURGO Metadata - Table Column Descriptions Report for more detailed descriptions of each column.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Metadata - Table Column Descriptions Report. File Name: SSURGO_Metadata_-_Table_Column_Descriptions.pdfResource Description: This report contains the descriptions of all columns in each database table. Please see SSURGO Metadata - Tables and Columns Report for a complete listing of all columns in each database table.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Data Dictionary. File Name: SSURGO 2.3.2 Data Dictionary.csvResource Description: CSV version of the data dictionary

These applications were developed, with support from the U.S. National Science Foundation, over more than a decade at The Evergreen State College (TESC) to address the needs of forest canopy researchers.

The tools include:

Databank Database Generator: Graphical tool to generate ecological databases from standard and custom database templates. Generated database includes data entry forms, data dictionary, and Ecological Metadata Language (EML) documents.

CanopyView: An interactive visualization tool designed to view tree structure, canopy coverage, and other data stored in Databank-generated databases.

This publication also includes images that were stored in a web content management system operated as part of the project website. (Image annotations from that system have not been recovered).

The FDA shall publish in a format that is understandable and not misleading to a lay person, and place on public display, a list of 93 harmful and potentially harmful constituents in each tobacco product and smoke established under section 904(e) of the TCA. CTP has determined the best means to display the data is web-based on FDA.GOV. The HPHC back-end database and template for industry will be created in a future release of eSubmissions. The scope of this project is to: Phase 1 (Current POP): 1) build a website to support the display of the HPHC constituents, 2) allow the user to access educational information about the health effects of the chemicals; Phase 2 (next POP): 1) allow users of the website to perform a search by brand and sub-brand, 2) display a report on the HPHCs contained in that tobacco product, and 3) create an admin module to allow for an import of HPHC data via an Excel spreadsheet and to update the list of constituents.

The Parkinson's Disease Handwriting Database (PaHaW) consists of multiple handwriting samples from 37 parkinsonian patients (19 men/18 women) and 38 gender and age-matched healthy controls (20 men/18 women). The database was acquired in cooperation with the Movement Disorders Center at the First Department of Neurology, Masaryk University and St. Anne's University Hospital in Brno, Czech Republic.

Each subject was asked to complete a handwriting/drawing protocol according to the prepared filled template at a comfortable speed. The protocol contains an Archimedean spiral, a grapheme, several words and a sentence. The completed template was shown to the subjects; no restrictions about the number of repetitions of syllables/words in tasks or their height were given.

A tablet was overlaid with an empty paper template (containing only printed lines and a square box specifying area for the Archimedean spiral), and a conventional ink pen was held in a normal fashion, allowing for immediate full visual feedback. The signals were recorded using the Intuos 4M (Wacom technology) digitizing tablet with 133 Hz sampling frequency.

Digitized signals were acquired during the movements executed while exerting pressure on the writing surface and during the movement above the writing surface. We denote these signals as on-surface movement and in-air movement, respectively. The perpendicular pressure exerted on the tablet surface was also recorded. The recordings started when the pen touched the surface of the digitizer and finished when the task was completed. The tablet captured the following signals (time series): x-coordinate; y-coordinate; timestamp; button status; pressure; tilt; and elevation. Button status is a binary variable, being 0 for pen-up state (in-air movement) and 1 for pen-down state (on-surface movement).

Mouse Brain MRI atlas (both in-vivo and ex-vivo) (repository relocated from the original webpage)

List of atlases

FVB_NCrl: Brain MRI atlas of the wild-type FVB_NCrl mouse strain (used as the background strain for the rTg4510 which is a tauopathy model mice express a repressible form of human tau containing the P301L mutation that has been linked with familial frontotemporal dementia.)

NeAt: Brain MRI atlas of the whld-type C57BL/6J mouse strain. Atlas was created based on the original MRM NeAt mouse brain atlas (template images reoriented and bias-corrected, left/right structure label seperated, and 4th ventricle manual segmentation added).

Tc1 Cerebellum: TC1 mouse cerebellar cortical sublayer lobules.This mouse cerebellar atlas can be used for mouse cerebellar morphometry.

Citation

If you use the segmented brain structure, or use the atlas along with the automatic mouse brain MRI segmentation tools, we ask you to kindly cite the following papers:

Ma D, Cardoso MJ, Modat M, Powell N, Wells J, Holmes H, Wiseman F, Tybulewicz V, Fisher E, Lythgoe MF, Ourselin S. Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion. PloS one. 2014 Jan 27;9(1):e86576. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086576

Ma D, Holmes HE, Cardoso MJ, Modat M, Harrison IF, Powell NM, O'Callaghan J, Ismail O, Johnson RA, O’Neill MJ, Collins EC, Mirza F. Beg, Karteek Popuri, Mark F. Lythgoe, and Sebastien Ourselin Study the longitudinal in vivo and cross-sectional ex vivo brain volume difference for disease progression and treatment effect on mouse model of tauopathy using automated MRI structural parcellation. Frontiers in Neuroscience. 2019;13:11. https://www.frontiersin.org/articles/10.3389/fnins.2019.00011

If you use the brain MR images of the FVB_NCrl mouse strain (the wildtype background of rTg4510), we ask you to kindly cite the following papers:

Wells JA, O'Callaghan JM, Holmes HE, Powell NM, Johnson RA, Siow B, Torrealdea F, Ismail O, Walker-Samuel S, Golay X, Rega M. In vivo imaging of tau pathology using multi-parametric quantitative MRI. Neuroimage. 2015 May 1;111:369-78. https://www.sciencedirect.com/science/article/pii/S105381191500124X

Holmes HE, Colgan N, Ismail O, Ma D, Powell NM, O'Callaghan JM, Harrison IF, Johnson RA, Murray TK, Ahmed Z, Heggenes M. Imaging the accumulation and suppression of tau pathology using multiparametric MRI. Neurobiology of aging. 2016 Mar 1;39:184-94. https://www.sciencedirect.com/science/article/pii/S0197458015006053

Holmes HE, Powell NM, Ma D, Ismail O, Harrison IF, Wells JA, Colgan N, O'Callaghan JM, Johnson RA, Murray TK, Ahmed Z. Comparison of in vivo and ex vivo MRI for the detection of structural abnormalities in a mouse model of tauopathy. Frontiers in neuroinformatics. 2017 Mar 31;11:20. https://www.frontiersin.org/articles/10.3389/fninf.2017.00020/full

If you're using the mouse MRI T2* Active Starining Cerebellar atlas, we ask you to please kindly cite the following papers:

Ma, D., Cardoso, M. J., Zuluaga, M. A., Modat, M., Powell, N. M., Wiseman, F. K., Cleary, J. O., Sinclair, B., Harrison, I. F., Siow, B., Popuri, K., Lee, S., Matsubara, J. A., Sarunic, M. V, Beg, M. F., Tybulewicz, V. L. J., Fisher, E. M. C., Lythgoe, M. F., & Ourselin, S. (2020). Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellum of the Tc1 mouse model of Down Syndrome – a comprehensive morphometric analysis with active staining contrast-enhanced MRI. NeuroImage, 117271. https://doi.org/https://doi.org/10.1016/j.neuroimage.2020.117271 Ma, D., Cardoso, M. J., Zuluaga, M. A., Modat, M., Powell, N., Wiseman, F., Tybulewicz, V., Fisher, E., Lythgoe, M. F., & Ourselin, S. (2015). Grey Matter Sublayer Thickness Estimation in the Mouse Cerebellum. In Medical Image Computing and Computer Assisted Intervention 2015 (pp. 644–651). https://doi.org/10.1007/978-3-319-24574-4_77

Reference

For the original information of the NeAt atlas, please please refer to the website: http://brainatlas.mbi.ufl.edu/, and the following two reference papers: Ma Yu, Smith David, Hof Patrick R, Foerster Bernd, Hamilton Scott, Blackband Stephen J, Yu Mei, Benveniste Helene In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy. Front. Neuroanat. 2, 1 (2008). Ma Yu, Hof P R, Grant S C, Blackband S J, Bennett R, Slatest L, McGuigan M D, Benveniste H A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy. Neuroscience 135, 1203–15 (2005).

Funding The works in this repositories received multiple funding from EPSRC, UCL Leonard Wolfson Experimental Neurology center, Medical Research Council (MRC), the NIHR Biomedical Research Unit (Dementia) at UCL and the National Institute for Health Research University College London Hospitals Biomedical Research center, the UK Regenerative Medicine Platform Safety Hub, and the Kings College London and UCL Comprehensive Cancer Imaging center CRUK & EPSRC in association with the MRC and DoH (England), UCL Faculty of Engineering funding scheme, Alzheimer Society Reseasrch Program from Alzheimer Society Canada, NSERC, CIHR, MSFHR Canada， Eli Lilly and Company, Wellcome Trust, the Francis Crick Institute, Cancer Research UK, and University of Melbourne McKenzie Fellowship.

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