3 datasets found
  1. Hospital Database Management System SQL Project

    • kaggle.com
    Updated May 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Andrew Dolcimascolo-Garrett (2024). Hospital Database Management System SQL Project [Dataset]. https://www.kaggle.com/datasets/andrewdolcigarrett/hospital-database-management-system-sql-project/versions/1
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Andrew Dolcimascolo-Garrett
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Andrew Dolcimascolo-Garrett

    Released under MIT

    Contents

  2. d

    Ramakrishnan: Semantics on the Web

    • catalog.data.gov
    • gimi9.com
    • +2more
    Updated Apr 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dashlink (2025). Ramakrishnan: Semantics on the Web [Dataset]. https://catalog.data.gov/dataset/ramakrishnan-semantics-on-the-web
    Explore at:
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Dashlink
    Description

    It is becoming increasingly clear that the next generation of web search and advertising will rely on a deeper understanding of user intent and task modeling, and a correspondingly richer interpretation of content on the web. How we get there, in particular, how we understand web content in richer terms than bags of words and links, is a wide open and fascinating question. I will discuss some of the options here, and look closely at the role that information extraction can play. Speaker Bio Raghu Ramakrishnan is Chief Scientist for Audience and Cloud Computing at Yahoo!, and is a Research Fellow, heading the Community Systems area in Yahoo! Research. He was Professor of Computer Sciences at the University of Wisconsin-Madison, and was founder and CTO of QUIQ, a company that pioneered question-answering communities, powering Ask Jeeves' AnswerPoint as well as customer-support for companies such as Compaq. His research has influenced query optimization in commercial database systems, and the design of window functions in SQL:1999. His paper on the Birch clustering algorithm received the SIGMOD 10-Year Test-of-Time award, and he has written the widely-used text "Database Management Systems" (with Johannes Gehrke). He is Chair of ACM SIGMOD, on the Board of Directors of ACM SIGKDD and the Board of Trustees of the VLDB Endowment, and has served as editor-in-chief of the Journal of Data Mining and Knowledge Discovery, associate editor of ACM Transactions on Database Systems, and the Database area editor of the Journal of Logic Programming. Ramakrishnan is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and has received several awards, including a Distinguished Alumnus Award from IIT Madras, a Packard Foundation Fellowship in Science and Engineering, an NSF Presidential Young Investigator Award, and an ACM SIGMOD Contributions Award.

  3. a

    Coal Mine Information System Features

    • data-indnr.hub.arcgis.com
    Updated Nov 9, 2015
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    InDNRMaps (2015). Coal Mine Information System Features [Dataset]. https://data-indnr.hub.arcgis.com/datasets/surface-mines
    Explore at:
    Dataset updated
    Nov 9, 2015
    Dataset authored and provided by
    InDNRMaps
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Coal Mine Information System Features includes 3 distinct layers: Mine Entries, Surface Mines, and Underground Mines. Please see the information below for each layer. For additional information, please visit the DNR Division of Reclamation's Coal Mine Information System website.Coal Mine Entries includes the locations of underground coal mine entrances in the coal region of west-central and southwestern Indiana. Coal_Mine_Entries_DNR_IN is a compilation of all documented underground coal mine entrances in Indiana. Coal_Mine_Entries_DNR_IN was compiled by the Indiana Geological Survey (IGS) as part of a contract deliverable for the Abandoned Mine Lands program of the Indiana Department of Natural Resources, Division of Reclamation. Coal_Mine_Entries_DNR_IN incorporates mine entrance locations compiled as part of the Indiana Coal Mine Information System (CMIS), an integrated geographic information system (GIS) and database management system (DBMS) created to store, analyze, and help distribute coal mine data in Indiana. The system contains data for surface and underground coal mines that operated in Indiana from the mid-1830s to 2007. Original source information for Coal_Mine_Entries_DNR_IN includes company mine maps, field maps and notes of IGS geologists, IGS publications, and Reports of the Indiana State Mine Inspector. All mine data included in Coal_Mine_Entries_DNR_IN are organized in a GIS using ESRI ArcGIS software of the Environmental Systems Research Institute (ESRI) on the Windows platform. Scale of source data ranges from 1:4,800 to 1:100,000.Surface Mines includes the location and extent of surface coal mines in the coal region of west-central and southwestern Indiana. Coal_Mine_Surface_DNR_IN is a composite of all surface mine locations in Indiana. It was compiled by the Indiana Geological Survey (IGS) as part of a contract deliverable for the Abandoned Mine Lands program of the Indiana Department of Natural Resources, Division of Reclamation. Coal_Mine_Surface_DNR_IN incorporates surface mine locations compiled by the IGS in the early 1980s with contemporary mine outlines digitized from affected-area maps collected from the Indiana Department of Natural Resources, Division of Reclamation and maps collected from the Indiana Bureau of Mines. Original source information for Coal_Mine_Surface_DNR_IN includes company mine maps, field maps and notes of IGS Geologists, IGS publications, several series of aerial photographs, and U.S. Geological Survey 7.5-minute quadrangle maps. All mine data included in Coal_Mine_Surface_DNR_IN are organized in a GIS using ArcGIS software of the Environmental Systems Research Institute (ESRI) on the Windows platform. Scale of source data ranges from 1:4,800 to 1:100,000. Coal_Mine_Surface_DNR_IN includes attributes which allow the mine polygons to be differentiated based on mine number, source information, and dates of mining.Underground Mines includes the location and extent of underground coal mines in the coal region of west-central and southwestern Indiana. Coal_Mine_Underground_DNR_IN is a composite of all underground mine locations in Indiana. It was compiled by the Indiana Geological Survey (IGS) as part of a contract deliverable for the Abandoned Mine Lands program of the Indiana Department of Natural Resources, Division of Reclamation. Coal_Mine_Underground_DNR_IN incorporates underground mine locations compiled by the IGS in the early 1980s with hundreds of historic underground mine locations digitized in 1998-1999 and contemporary mine outlines digitized from maps collected from coal companies or the Indiana Bureau of Mines. Original source information for Coal_Mine_Underground_DNR_IN includes company mine maps, field maps and notes of IGS geologists, IGS publications, and Indiana State Mine Inspector Reports. All mine data included in Coal_Mine_Underground_DNR_IN are organized in a GIS using ESRI ArcGIS software of the Environmental Systems Research Institute (ESRI) on the Windows platform. Scale of source data ranges from 1:4,800 to 1:100,000. Coal_Mine_Underground_DNR_IN includes attributes which allow the mine polygons to be differentiated based on mine type, mine number, source information, and dates of mining.DATA DISCLAIMER: These data were compiled by Indiana Department of Natural Resources, Division of Reclamation, using data believed to be accurate; however, a degree of error is inherent in all data. This product is distributed "AS-IS" without warranties of any kind, either expressed or implied, including but not limited to warranties of suitability of a particular purpose or use. No attempt has been made in either the designed format or production of these data to define the limits or jurisdiction of any federal, state, or local government. These data are intended for use only at the published scale or smaller and are for reference purposes only. They are not to be construed as a legal document or survey instrument. A detailed on-the-ground survey and historical analysis of a single site may differ from this data.

  4. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Andrew Dolcimascolo-Garrett (2024). Hospital Database Management System SQL Project [Dataset]. https://www.kaggle.com/datasets/andrewdolcigarrett/hospital-database-management-system-sql-project/versions/1
Organization logo

Hospital Database Management System SQL Project

A Data Mining Exercise in SQL

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 9, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Andrew Dolcimascolo-Garrett
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

Dataset

This dataset was created by Andrew Dolcimascolo-Garrett

Released under MIT

Contents

Search
Clear search
Close search
Google apps
Main menu