damien-johnston/open-data-project dataset hosted on Hugging Face and contributed by the HF Datasets community

the Department of Energy’s Enterprise Project Management Organization (EPMO), providing leadership and assistance in developing and implementing DOE-wide policies, procedures, programs, and management systems pertaining to project management, and independently monitors, assesses, and reports on project execution performance. The office validates project performance baselines–scope, cost and schedule–of the Department’s largest construction and environmental clean-up projects prior to budget request to Congress—an active project portfolio totaling over $30 billion. The office also serves as Executive Secretariat for the Department’s Energy Systems Acquisition Advisory Board (ESAAB) and the Project Management Risk Committee (PMRC). In these capacities, the Director is accountable to the Deputy Secretary.

Dataset

This dataset was created by Jordan Hill NMTAFE

Released under MIT

Contents

N/A

International projects targeting Jordanians and Syrians and providing them with job opportunities in some disciplines

Machine learning (ML) has gained much attention and has been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such high-quality dataset poses an obstacle to understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on evidences of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. In this repository we provide "NICHE.csv" file that contains the list of the project names along with their labels, descriptive information for every dimension, and several basic statistics, such as the number of stars and commits. This dataset can help researchers understand the practices that are followed in high-quality ML projects. It can also be used as a benchmark for classifiers designed to identify engineered ML projects.

GitHub page: https://github.com/soarsmu/NICHE

Dataset

This dataset was created by Glitch_in_Vector

Contents

Chunk_0 for me, Choose others as you want.

City of Pittsburgh Capital Projects Budgets NOTE: The data in this dataset has not updated since 2021 because of a broken data feed. We're working to fix it.

United States Department of Transportation Public Data Listing. The file is formatted to comply with project open data common core metadata requirements (http://project-open-data.github.io/schema/) and conforms to schema version 1.1

This dataset is constructed from project activity experience.

Columns: not done - Projects that didn't worked out until accomplishment (0 = done // 1 = not done) time required - Time in hours estimated for the accomplishment cost - Cost per hour

Coups d'Ètat are important events in the life of a country. They constitute an important subset of irregular transfers of political power that can have significant and enduring consequences for national well-being. There are only a limited number of datasets available to study these events (Powell and Thyne 2011, Marshall and Marshall 2019). Seeking to facilitate research on post-WWII coups by compiling a more comprehensive list and categorization of these events, the Cline Center for Advanced Social Research (previously the Cline Center for Democracy) initiated the Coup d’État Project as part of its Societal Infrastructures and Development (SID) project. More specifically, this dataset identifies the outcomes of coup events (i.e., realized, unrealized, or conspiracy) the type of actor(s) who initiated the coup (i.e., military, rebels, etc.), as well as the fate of the deposed leader. Version 2.1.3 adds 19 additional coup events to the data set, corrects the date of a coup in Tunisia, and reclassifies an attempted coup in Brazil in December 2022 to a conspiracy. Version 2.1.2 added 6 additional coup events that occurred in 2022 and updated the coding of an attempted coup event in Kazakhstan in January 2022. Version 2.1.1 corrected a mistake in version 2.1.0, where the designation of “dissident coup” had been dropped in error for coup_id: 00201062021. Version 2.1.1 fixed this omission by marking the case as both a dissident coup and an auto-coup. Version 2.1.0 added 36 cases to the data set and removed two cases from the v2.0.0 data. This update also added actor coding for 46 coup events and added executive outcomes to 18 events from version 2.0.0. A few other changes were made to correct inconsistencies in the coup ID variable and the date of the event. Version 2.0.0 improved several aspects of the previous version (v1.0.0) and incorporated additional source material to include: • Reconciling missing event data • Removing events with irreconcilable event dates • Removing events with insufficient sourcing (each event needs at least two sources) • Removing events that were inaccurately coded as coup events • Removing variables that fell below the threshold of inter-coder reliability required by the project • Removing the spreadsheet ‘CoupInventory.xls’ because of inadequate attribution and citations in the event summaries • Extending the period covered from 1945-2005 to 1945-2019 • Adding events from Powell and Thyne’s Coup Data (Powell and Thyne, 2011)
Items in this Dataset 1. Cline Center Coup d'État Codebook v.2.1.3 Codebook.pdf - This 15-page document describes the Cline Center Coup d’État Project dataset. The first section of this codebook provides a summary of the different versions of the data. The second section provides a succinct definition of a coup d’état used by the Coup d'État Project and an overview of the categories used to differentiate the wide array of events that meet the project's definition. It also defines coup outcomes. The third section describes the methodology used to produce the data. Revised February 2024 2. Coup Data v2.1.3.csv - This CSV (Comma Separated Values) file contains all of the coup event data from the Cline Center Coup d’État Project. It contains 29 variables and 1000 observations. Revised February 2024 3. Source Document v2.1.3.pdf - This 325-page document provides the sources used for each of the coup events identified in this dataset. Please use the value in the coup_id variable to identify the sources used to identify that particular event. Revised February 2024 4. README.md - This file contains useful information for the user about the dataset. It is a text file written in markdown language. Revised February 2024
Citation Guidelines 1. To cite the codebook (or any other documentation associated with the Cline Center Coup d’État Project Dataset) please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Scott Althaus. 2024. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7 2. To cite data from the Cline Center Coup d’État Project Dataset please use the following citation (filling in the correct date of access): Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Emilio Soto. 2024. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7

International projects aimed at training Syrian refugees in some disciplines, including agriculture and other fields.

This dataset was originally collected for a data science and machine learning project that aimed at investigating the potential correlation between the amount of time an individual spends on social media and the impact it has on their mental health.

The project involves conducting a survey to collect data, organizing the data, and using machine learning techniques to create a predictive model that can determine whether a person should seek professional help based on their answers to the survey questions.

This project was completed as part of a Statistics course at a university, and the team is currently in the process of writing a report and completing a paper that summarizes and discusses the findings in relation to other research on the topic.

The following is the Google Colab link to the project, done on Jupyter Notebook -

https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN

The following is the GitHub Repository of the project -

https://github.com/daerkns/social-media-and-mental-health

Libraries used for the Project -

Pandas
Numpy
Matplotlib
Seaborn
Sci-kit Learn

This dataset contains capital commitment plan data by managing agency, project identification number and project schedules. The dataset was updated three times a year during the Preliminary, Executive and Adopted Capital Commitment Plans. Starting in January 2024, OMB will no longer update this dataset. It is being replaced by the Capital Projects Dashboard administered by the Mayor's Office of Operations.

Ipsos Public Affairs conducted the Twitter Survey in 2018 to analyze public attitudes, behaviors, and opinions related to Twitter usage. The survey explores patterns of engagement, demographic differences, and the platform’s influence on news consumption and communication trends.

This webinar provides information on the federal government’s role in the process of building a successful child welfare information system and includes resources and guidance available to support states, territories, and tribes.

Metadata-only record linking to the original dataset. Open original dataset below.

Get data on announced projects funded through the Rural Economic Development (RED) program.

Ontario's RED program funds projects that stimulate economic growth in rural and Indigenous communities.

The data includes:

• name of the organization that requested funding
• county or district where the organization is located
• project name
• date that funding was approved
• amount of funding provided

From 2013 to 2016, the RED program funded projects led by businesses or communities.

Starting in 2017, the RED program only focuses on projects led by:

• not-for-profit organizations
• municipalities
• local service boards
• Indigenous communities and organizations

Learn more about the Rural Economic Development program.

Researchers in the social sciences use various software for statistical analysis of rectangular, structured data. The various data formats which are only partially compatible impede data exchange and reuse. In particular, proprietary data formats endanger those in the FAIR principles enshrined demand for interoperability. The open, metadata-enriched, non-proprietary data dissemination format (OpenDF) is a project of KonsortSWD, the NFDI consortium for the social, behavioural, educational and economic sciences. The project provides a non-proprietary Open Data Format enriched with multi-level metadata that is smoothly usable with popular statistical software. The project includes two main work aspects: first, the specification of the Open Data Format, including its metadata components, and second, its technical implementation for various statistical software packages. This presentation will highlight the current phase of our work. First, we will present the specification of metadata profile for the Open Data Format, which is fully compatible with the DDI Codebook. In addition, based on this profile, we will demonstrate the technical import and export filters for specific statistical program.

Red rated Large Projects - CYC. RAG (red-amber-green) project rating is used in project management for indicating the progress of projects. This measure shows the number of council's large projects we are currently working to deliver which one or more aspects of project viability (time, cost, scope) exceed tolerances set by the project board. The council qualifies a project as "large" if it achieves a score of 106 or more out of the 160 on the Project Assessment Matrix. The matrix takes into consideration the duration of project, budget used and number of people involved as well as the impact on the council's reputation.

Locations of current participants in Detroit's Project Greenlight as September 24, 2019. File was originally created on October 17, 2017 and was obtained from the city's Open Data Portal on October 1, 2019.