This data can also be viewed at https://data-housinggovie.opendata.arcgis.com/

This layer represents projected land use in the year 2040. Data were prepared and submitted as part of the City of Tempe's General Plan 2040.Contact E-Mail: data@tempe.govLink to department home page: https://www.tempe.gov/planningData Source: Spatial DatabaseData Source Type: GeospatialPreparation Method: Created based off documentation in current and previous General PlansPublish Frequency: As NecessaryPublish Method: AutomaticLink to Data Dictionary

This data package aims to pilot an approach for providing usable data for analyses related to drought planning and management for urban water suppliers--ultimately contributing to improvements in communication around drought. This project was convened by the California Water Data Consortium in partnership with the Department of Water Resources (DWR) and the State Water Resources and Control Board (SWB) and is one of two use cases of this working group that aim to improve data submitted by urban water suppliers in terms of accessibility and useability. The datasets from DWR and the SWB are compiled in a standard format to allow interested parties to synthesize and analyze these data into a cohesive message. This package includes a data management plan describing its development and maintenance. All code related to preparing this data package can be found on GitHub. Please note that the "org_id" (DWR's Organization ID) and the "pwsid" (SWB's Public Water System ID) can be used to connect to the various data tables in this package.

We acknowledge that data quality issues may exist. Making these data available in a usable format will help identify and address data quality issues. If you identify any data quality issues, please contact the data steward (see contact information). We plan to iteratively update this data package to incorporate new data and to update existing data with quality fixes. The purpose of this project is to demonstrate how data from two agencies, when made publicly available, can be used in relevant analyses; if you found this data package useful, please contact the data steward (see contact information) to share your experience.

San Francisco Planning Department's Planning Areas.

Graphic data of Town Planning Board (TPB) Planning Guidelines No. 12C for Application for Developments within Deep Bay Area under Section 16 of the Town Planning Ordinance, including all geographical information system (GIS) data, data dictionary and guidelines on using the GIS data, provided by the TPB is available for download. Please note that in using the data, you have agreed to be bound unconditionally by the Terms and Conditions of Use of the digital planning data enclosed in the downloaded data. Please read carefully the Terms and Conditions of Use. Please click https://www.info.gov.hk/tpb/en/forms/Guidelines/pg12c_e.pdf to download the TPB Planning Guidelines No.12C. For details of the graphic data, please refer to Statutory Planning Portal 3 website (http://www.ozp.tpb.gov.hk). The multiple file formats are available for dataset download in API.

This dataset contains information about financial plan initiatives amounts applied during a financial plan period. The dollar amounts are rounded to thousands. This dataset is updated four times per year after publication of the First Quarter, Preliminary, Executive and Adopted Financial Plan, usually in November, January, April and June respectively.

Dataset Summary About this data: Planning is responsible for monitoring physical, social and economic factors relevant to the well being of the City. The Office provides consultant services to City departments and community organizations for planning related projects and topics. This layer provides the boundaries of areas where a community or neighborhood plan has been developed, or is in process of development. Each feature provides a link to a website or actual plan for more information. For more information please visit: https://www.cityofrochester.gov/planning.aspx Dictionary: Project Name: The name of the planning project. Project Description: Notes the specific goals of the project. Website: The link to the relevant City of Rochester web page that provides more detail on a given project. Contact: The contact person for a given project. Organization: The group responsible for carrying out the project. Funding Source: Identifies the organization responsible for providing financial resources to cover the expenses of a project. Contact Email: The email for the Contact person (if available). Project Year: The year the project started. Project Status: Identifies the current progress of a given project (In progress, Completed, Ongoing, Not Started). City Lead: Notes if the City of Rochester is the primary project lead for a given project (Yes/No). ACTIVE: Notes whether or not the project is active or completed. COLOR: The color chosen to represent the project on the Development Projects and Plans application. Link Text: Contains “More information” as a hyperlink to the project website. Shape_Area: The built-in geometry field that holds the area of the shape. Shape_Length: The built-in geometry field that holds the length of the shape. Source: This data comes from the City of Rochester’s Office of Planning.

The PDB is a database of U.S. housing, demographic, socioeconomic and operational statistics based on select 2010 Decennial Census and select 5-year American Community Survey (ACS) estimates. Data are provided at the census tract level of geography. These data can be used for many purposes, including survey field operations planning.

This dataset is related with the Data in Brief article entitled: “A benchmark dataset for the retail multiskilled personnel planning under uncertain demand”, which was submitted to Data in Brief Journal. This data article describes datasets from a home improvement retail store located in Santiago, Chile. The datasets have been developed to solve a multiskilled personnel assignment problem (MPAP) under uncertain demand. Particularly, this database is related to the published article "Multiskilled personnel assignment problem under uncertain demand: A benchmarking analysis" developed by Henao et al. (2022).

The datasets contain real and simulated data. Regarding the real dataset, it includes information about the store size, number of employees, employment-contract characteristics, mean value of weekly hours demand in each department, and cost parameters. Regarding the simulated datasets, they include information about the random parameter of weekly hours demand in each store department. The simulated data are presented in 18 text files classified by: (i) Sample type (in-sample or out-of-sample). (ii) Truncation-type method (zero-truncated or percentile-truncated). (iii) Coefficient of variation (5, 10, 20, 30, 40, 50%).

Scientific Data Management (SDM) Program shares and manages scientific and scientific program information systems in ways that support the mission and business of the NWFSC. We strive to bring quality information, in the right form, to the right people at the right time to support necessary decisions and generate ideas. Multi-FMC annual project planning (for budget, people, and operational costs) and data set tracking (for data entry to feed InPort/NCEI/Data.gov) TEST CASE TWO.

Digital planning data, including all geographical information system (GIS) data, data dictionary and guidelines on using the GIS data, provided by the Town Planning Board (the Board) is available for download. Please note that in using the data, you have agreed to be bound unconditionally by the Terms and Conditions of Use of the digital planning data enclosed in the downloaded data. Please read carefully the Terms and Conditions of Use. For details of statutory plans, please refer to Statutory Planning Portal 3 website (http://www.ozp.tpb.gov.hk). The multiple file formats are available for dataset download in API.

These are grouping of census tracts. Planning Districts are used in various areas of the Planning process, mainly for analysis and management but are also in some parts of the General Plan.

27 sheets of data, each sheet representing a table from the database that stores the information. The order of the sheets is based on the sequence of reporting forms for the Financial Transactions Report.

This COVADIS data standard concerns local planning documents (LDPs) and land use plans (POSs that are PLU). This data standard provides a technical framework describing in detail how to dematerialise these planning documents into a spatial database that can be used by a GIS tool and interoperable. This standard of COVADIS data was developed on the basis of the specifications for the dematerialisation of planning documents updated in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The dematerialisation of the graphic documents of a PLU, POS generates a set of spatial data composed of several catalogues of objects: Class ZONE_URBA containing the urban areas corresponding to the zoning plan of the PLU (R.123-5 to 8): urban areas (U), areas to be urbanised (AU), agricultural areas (A) and natural and forest areas (N). A regulation is attached to each area. The by-law may lay down different rules, depending on whether the purpose of the constructions will relate to housing, hotel accommodation, offices, trade, crafts, industry, agricultural or forestry operations or warehouse functions. Class PRESCRIPTION containing all surface, linear and point requirements for PLU or POS (R123-11). They are superimposed on an area in the planning document and in general impose an additional constraint on the settlement of the area. A regulation shall be attached to each prescription.

OCIO policy 187 requires agencies to adopt open data plans annually. This table identifies the plans received by OCIO.

This COVADIS data standard concerns local planning documents (LDPs) and land use plans (POSs that are PLU). This data standard provides a technical framework describing in detail how to dematerialise these planning documents into a spatial database that can be used by a GIS tool and interoperable. This standard of data concerns both the graphic zoning plans, the superimposed requirements and the regulations applying to each type of area.This standard of COVADIS data was developed on the basis of the specifications for the dematerialisation of urban planning documents updated in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The COVADIS data standard provides definitions and a structure for organising and storing existing PLU/POS spatial data in an infrastructure in digital form, while the CNIG specification serves to frame the digitisation of such data. The ‘Data Structure’ section presented in this COVADIS standard provides additional recommendations for the storage of data files (see Part C). These are choices specific to the MAA and MEDDE data infrastructure that do not apply outside their context. Communal maps are the subject of another COVADIS data standard.

NOTE: To review the latest plan, make sure to filter the "Report Year" column to the latest year.

Data on public websites maintained by or on behalf of the city agencies.

This COVADIS data standard concerns local planning documents (LDPs) and land use plans (POSs that are PLU). This data standard provides a technical framework describing in detail how to dematerialise these planning documents into a spatial database that can be used by a GIS tool and interoperable. This standard of data concerns both the graphic zoning plans, the superimposed requirements and the regulations applying to each type of area.This standard of COVADIS data was developed on the basis of the specifications for the dematerialisation of urban planning documents updated in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The COVADIS data standard provides definitions and a structure for organising and storing existing PLU/POS spatial data in an infrastructure in digital form, while the CNIG specification serves to frame the digitisation of such data. The ‘Data Structure’ section presented in this COVADIS standard provides additional recommendations for the storage of data files (see Part C). These are choices specific to the MAA and MEDDE data infrastructure that do not apply outside their context. Communal maps are the subject of another COVADIS data standard.