AndreaBozzo/ceres-open-data-index huggingface dataset:
3.12 Municipal Equality Index Score (summary)

Cities are in constant competition for residents, businesses, and employees, and inclusiveness is a crucial factor that attracts all three. The Municipal Equality Index (MEI) specifically measures laws and policies of municipalities to examine how inclusive cities are of LGBTQ (Lesbian, Gay, Bisexual, Transgender, and Questioning) people. Administered by the Human Rights Campaign, the MEI scorecard criteria annually evaluate a municipality on six categories, with bonus points available: 1. Non-Discrimination Laws: This category evaluates whether discrimination based on sexual orientation and gender identity is prohibited by city, county, or state in areas of employment m housing, and public accommodations. 2. Relationship Recognition: Marriage, civil unions, and comprehensive domestic partnerships are matters of state policy; cities and counties have only the power to create domestic partner registries. 3. Municipality as Employer: By offering equivalent benefits and protections to LGBTQ employees, and by awarding contracts to fair-minded businesses, municipalities commit themselves to treating LGBTQ employees equally. 4. Municipal Services: The section assesses the efforts of the city to ensure LGBTQ constituents are included in city services and programs. 5. Law Enforcement: Fair enforcement of the law includes responsible reporting of hate crimes and engaging with the LGBTQ community in a thoughtful and respectful way. 6. Relationship with the LGBTQ Community: This category measures the city leadership’s commitment to fully include the LGBTQ community and to advocate for full equality. Additional information available at [hrc.org/mei] This page provides data for the Municipality Equality Index performance measure. The performance measure dashboard is available at [3.12 Municipal Equality Index]. Additional Information Source: Contact: Wydale Holmes Contact E-Mail: wydale_holmes@tempe.gov Data Source Type: Excel Preparation Method: Publish Frequency: Annually, October Publish Method: Manual [Data Dictionary ]
3.27 Traffic Delay Reduction (summary)

The city is using Travel Time Index as a measure to quantify traffic delay in the city. The Travel Time Index is the ratio of the travel time during the peak period to the time required to make the same trip at free-flow speeds. It should be noted that this data is subject to seasonal variations. The 2020 Q2 and Q3 data includes the summer months when traffic volumes are lower, thus the Travel Time Index is improved in these quarters. The performance measure page is available at [3.27 Traffic Delay Reduction]. Additional Information Source: Bluetooth ARID sensors Contact (author): Cathy Hollow Contact E-Mail (author): catherine_hollow@tempe.gov Contact (maintainer): Contact E-Mail (maintainer): Data Source Type: Table, CSV Preparation Method: Peak period data is manually extracted. The travel time index calculation is the peak period data divided by the free flow data (constant per segment). Publish Frequency: Quarterly Publish Method: Manual [Data Dictionary]
General Offenses (Open Data)

The General Offense Crime Report Dataset includes criminal and city code violation offenses which document the scope and nature of each offense or information gathering activity. It is used to computate the Uniform Crime Report Index as reported to the Federal Bureau of Investigation and for local crime reporting purposes. [Contact E-mail] Link: N/A Data Source: Versaterm Informix RMS \ Data Source Type: Informix and/or SQL Server Preparation Method: Preparation Method: Automated View pulled from SQL Server and published as hosted resource onto ArcGIS Online Publish Frequency: Weekly Publish Method: Automatic [Data Dictionary]
Code Complaints

This feature layer contains records of code complaints in the City of Tempe. Records are updated weekly on Monday mornings at approximately 2:30 a.m. local time using the most recent data available from the Accela system. As a result, there may be a delay of up to one week (or slightly longer) between activity in Accela and its appearance in this dataset. Please note that there may be multiple complaint records associated with a single address point. When viewing these data using GIS software, multiple records per address result in stacked points on the map. Data are provided in this exploded format to make it easier for users. The data found here are displayed at [https://experience.arcgis.com/experience/c9f7133c457e4ce08c1224f5d84addb9] albeit in a non-exploded form where points aren't stacked. [Contact Email] Link: [www.tempe.gov/code] Data Source: Accela Data Source Type: Geospatial Publish Frequency: Weekly Publish Method: Automatic (via ETL)
2.08 Treatment Court Satisfaction (detail)

Tempe Municipal Court continuously assesses its Treatment Court programs, gathering feedback through participant surveys for improvement and enhancing participant success rates. The Mental Health Court, a collaborative effort among the judge, prosecutor, defense attorney, and treatment team, addresses the unique needs of participants with mental illness and developmental disabilities. It deals with pending charges and life situations, providing individualized treatment to reduce reoffending and improve participants' quality of life. The East Valley Regional Veterans Court, involving Chandler, Carefree-Cave Creek, Fountain Hills, Gilbert, Paradise Valley, Scottsdale, and Tempe Municipal Courts, aims to improve the quality of life for Arizona Veterans. A collaborative effort addresses pending charges and life situations, expediting access to Veteran-specific resources and ensuring Veterans meet obligations through tailored plans. Treatment is conducted through the United States Department of Veterans Affairs and Social Services agencies. Additional Information: Primary Contact: Marcos Romero Contact Email: Marcos_Romero@tempe.gov Data Source: Paper handout and online survey Data Source Type: Excel Preparation Method: Survey provided participants in electronic and paper-form at the completion of the program Publish Method: Manual Publish Frequency: Monthly [Data Dictionary]
2.08 Treatment Court Satisfaction (summary)

Tempe Municipal Court continuously assesses its Treatment Court programs, gathering feedback through participant surveys for improvement and enhancing participant success rates. The Mental Health Court, a collaborative effort among the judge, prosecutor, defense attorney, and treatment team, addresses the unique needs of participants with mental illness and developmental disabilities. It deals with pending charges and life situations, providing individualized treatment to reduce reoffending and improve participants' quality of life. The East Valley Regional Veterans Court, involving Chandler, Carefree-Cave Creek, Fountain Hills, Gilbert, Paradise Valley, Scottsdale, and Tempe Municipal Courts, aims to improve the quality of life for Arizona Veterans. A collaborative effort addresses pending charges and life situations, expediting access to Veteran-specific resources and ensuring Veterans meet obligations through tailored plans. Treatment is conducted through the United States Department of Veterans Affairs and Social Services agencies. The performance measure dashboard is available at [2.08 Treatment Court Satisfaction]. Additional Information Source: Participant Survey Contact: Marcos Romero Contact E-Mail: Marcos_Romero@tempe.gov Data Source Type: Excel Preparation Method: Survey administered, results manually compiled Publish Frequency: Monthly Publish Method: Manual [Data Dictionary]
4.19 Carbon Neutrality (summary)

This page provides data for the Carbon Neutrality performance measure. The City of Tempe is committed to protecting the environment. Carbon emissions are a significant contributor to the pollution of our atmosphere. Sources of carbon emissions include the energy used in city buildings and facilities, and in the fuel used in transit, city vehicles, and employee commuting. This performance measure puts the City on a path to being a carbon-neutral city. The municipal carbon footprint includes buildings, streetlights, water treatment, electricity, and fuel usage for fleet, transit, solid waste, and employee commute. The performance measure dashboard is available at [4.19 Carbon Neutrality]. Additional Information Source: City pisions: fleet, WUD, solid waste. APS, SRP, MAG, SHROG, and Valley Metro Contact: Grace Kelly Contact E-Mail: Grace_Kelly@tempe.gov Data Source Type: CSV Preparation Method: It is part of a larger data set and uses proprietary software. Publish Frequency: Every 5 years Publish Method: Manual [Data Dictionary]
4.18 Community Carbon Neutrality (summary)

As a commitment to sustainability, our city joined the Global Covenant of Mayors for Climate and Energy. Tempe is setting a path to sustainability and resilience with our first-ever Climate Action Plan (CAP). This CAP serves as a guideline for the City of Tempe’s path toward a sustainable and resilient future that will benefit the entire city. It is a detailed framework for measuring and reducing GHG emissions and climate change impacts. The CAP includes an inventory of previous years’ GHG emissions, Tempe’s emissions reduction goals, and prioritized actions. This dataset provides the community with Greenhouse Gas emissions for the City of Tempe. Community greenhouse gas emissions inventories are a way for cities to track community greenhouse gas emissions. Currently, cities consume over two-thirds of the world's energy and account for more than 70% of global CO2 emissions. (ICLEI) Tempe conducted a greenhouse gas inventory based on 2015 calendar year data to measure the community's greenhouse gas emissions. City staff worked with a consultant who recommended re-evaluating baseline data, from 2015. 2015 data has been updated accordingly. This page provides data for the Community Carbon Neutrality performance measure. The performance measure dashboard is available at [4.18 Community Carbon Neutrality]. Additional Information Source: Various sources including municipal resources, APS, SRP, SW Gas, and Maricopa Association of Governments. Contact (author): Grace Kelly Contact E-Mail (author): Grace_Kelly@tempe.gov Contact (maintainer): Braden Kay Contact E-Mail (maintainer): Braden_Kay@tempe.gov Data Source Type: Table Preparation Method: Transportation, fuel, and energy use data are collected from various sources for residential, commercial, and industrial uses in the community, and estimates of the amount of emissions are calculated using the ICLEI's ClearPath tool. Publish Frequency: Every 5 years Publish Method: Manual [Data Dictionary]
4.20 Community Development Process Satisfaction (summary) - retired

The Community Development Process Survey is an evaluation tool showing the City Council and the community our customer satisfaction levels during the course of processing an application. By collecting the survey responses, we can identify areas of satisfaction as well as steps for improvement. This dataset comes from collecting survey responses at each key step in the planning entitlement, plan review, permitting, and inspection processes. The performance measure page is available at [4.20 Community Development Process Satisfaction]. Additional Information Source: SurveyMonkey Contact (author): Jacob Payne Contact E-Mail (author): jacob_payne@tempe.gov Contact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel Preparation Method: Survey Monkey Publish Frequency: Annual Publish Method: Manual [Data Dictionary]
Zoning District

Zoning districts classify, regulate and restrict uses, as well as combine uses and encourage the location of compatible land uses close to one another. The district regulations provide development standards pertaining to the intensity of land uses and development, height and bulk of buildings and structures, and area of yards and other open areas between buildings and structures. Contact: Jacob Payne [Contact E-mail] Contact Phone: 480-350-8690 Link: N/A Data Source: ArcGIS Server, SQL Server Data Source Type: Geospatial Preparation Method: N/A Publish Frequency: As information changes Publish Method: Automatic [Data Dictionary]
Tree Inventory

This dataset includes Tempe’s tree inventory data and benefits of the trees as calculated by i-Tree Eco in October 2021. The dataset was put together by West Coast Arborists, Inc. (WCA) in 2021. About Tempe's Tree Inventory and i-Tree Eco This dataset contains the point locations and attributes of trees within City of Tempe and Facilities. The point dataset was originally collected by WCA, Inc. in 2017 and is routinely updated by WCA and the City of Tempe. The attributes used included TreeID, Exact DBH, Height Range, Exact Height, Condition, Botanical Name, Common Name, Latitude, and Longitude. Updates to the Tempe's point layer was made using the results from i-Tree Eco. An i-Tree Eco Analysis was run in September 2021 using i-Tree Eco v6.0.22 and the results were joined based on unique tree ID to Tempe's Tree inventory. The results from i-Tree Eco were added as attributes to the Tempe's Tree inventory. Attributes added were: Structural Value ($), Carbon Storage (lb), Carbon Storage ($), Gross Carbon Sequestration (lb/yr), Gross Carbon Sequestration ($/yr), Avoided Runoff (cubicFT/yr), Avoided Runoff ($/yr), Pollution Removal (oz/yr), Pollution Removal ($/yr) , Total Annual Benefits ($/yr), Height (ft), Canopy Cover (sqft), Tree Condition, Leaf Area (sqft), Leaf Biomass (lb), Leaf Area Index Basal Area (sqft), Cond, i-Tree_ID_BotName, i-Tree_ID_ComName and i-Tree_ID Genus. The exact definitions, meanings, calculations, etc. for the i-Tree Values can be found on i-Tree’s website via the i-Tree Eco User Manual. i-Tree Eco. i-Tree Software Suite v6.x. Web. Fall 2021. [https://www.itreetools.org] i-Tree Eco Manual: [https://www.itreetools.org/documents/275/EcoV6_UsersManual.2021.09.22.pdf] Tempe Tree and Shade Coverage (data hub site): [https://urbanforestry.tempe.gov/] Additional Information Source: West Coast Arborists, Inc. (WCA) 2021; i-Tree Eco v6 2021 Contact: Richard Adkins Contact E-Mail: richard_adkins@tempe.gov Data Source Type: GPS and Google map data; tables in CVS and Excel format Preparation Method: Field observations and records of individual trees; value calculations based on i-Tree Eco v6 found at [https://www.itreetools.org/support/resources-overview/i-tree-manuals-workbooks] Publish Frequency: Every 5 years or as data becomes available Publish Method: Manual [Data Dictionary]
Police Transparency - Arrests - All Data (main table / denormalized)

Main Table / Denormalized Version This dataset provides demographic information related to arrests made by the Tempe Police Department. Each record represents an individual charge associated with an arrest and includes details about both the person arrested (arrestee) and the arresting officer. Demographic fields include race and ethnicity, age range at the time of arrest, and gender for each party. The data is sourced from the Police Department’s Records Management System (RMS) and supports analysis of patterns related to arrests, enforcement activity, and demographic trends over time. This information is a component of ongoing efforts to promote transparency and provide context for law enforcement within the community. For detailed guidance on interpreting arrest counts and demographic breakdowns, please refer to the [User Guide: Understanding the Arrests Demographic Datasets]. Why this Dataset is Organized this Way? The main arrests open data table includes key information from each arrest event, along with associated person and charge details in one place. This format is ideal for quick viewing and simple analysis. Providing this format supports a wide range of users, from casual data explorers to experienced analysts. Understanding the Arrests Open Data (main table / denormalized version) Each row in this dataset represents a single charge, which means a single arrest event may appear multiple times if multiple charges were filed. To determine the number of unique arrests, users should perform a distinct count of the rin field, which serves as the arrest incident identifier. Likewise: * To count unique arrestees, use a distinct count of the pin field (person identifier). * To count unique arresting officers, use a distinct count of the arrest_officer field. This structure enables users to explore charge-level detail while maintaining the ability to summarize demographic data by arrest event, arrestee, or officer as needed. Visit the [User Guide: Understanding the Arrests Demographic Datasets] for more details. [Data Dictionary] Additional Information Contact Email: [PD-DataRequest@tempe.gov] Contact Phone: N/A Link: N/A Data Source: Versaterm RMS Data Source Type: SQL Server Preparation Method: Automated process Publish Frequency: Daily Publish Method: Automatic
Police Transparency - Arrests - All Data (related tables / normalized)

Related Tables / Normalized Version This dataset provides demographic information related to arrests made by the Tempe Police Department. Demographic fields include race and ethnicity, age range at the time of arrest, and gender for each party. The data is sourced from the Police Department’s Records Management System (RMS) and supports analysis of patterns related to arrests, enforcement activity, and demographic trends over time. This information is a component of ongoing efforts to promote transparency and provide context for law enforcement within the community. For detailed guidance on interpreting arrest counts and demographic breakdowns, please refer to the [User Guide: Understanding the Arrest Demographic Datasets - Related Tables]. Why this Dataset is Organized this Way? The related tables such as persons, charges, and locations follow a normalized data model. This structure is often preferred by data professionals for more advanced analysis, filtering, or joining with external datasets. Providing this format supports a wide range of users, from casual data explorers to experienced analysts. Understanding the Arrests Data (as related tables) The related tables represent different parts of the arrest data. Each one focuses on a different type of information, like the officers, individuals arrested, charges, and arrest details. All of these tables connect back to the arrests table, which acts as the central record for each event. This structure is called a normalized model and is often used to manage data in a more efficient way. Visit the [User Guide: Understanding the Arrest Demographic Datasets - Related Tables] for more details outlining the relationships between the related tables. [Data Dictionary] Additional Information Contact Email: [PD-DataRequest@tempe.gov] Contact Phone: N/A Link: N/A Data Source: Versaterm RMS Data Source Type: SQL Server Preparation Method: Automated process Publish Frequency: Daily Publish Method: Automatic
Police Transparency - Arrests - Last 90 Days (Dataset)

Main Table / Denormalized Version (last 90 days only) This dataset provides demographic information related to arrests made by the Tempe Police Department. Each record represents an individual charge associated with an arrest and includes details about both the person arrested (arrestee) and the arresting officer. Demographic fields include race and ethnicity, age range at the time of arrest, and gender for each party. The data is sourced from the Police Department’s Records Management System (RMS) and supports analysis of patterns related to arrests, enforcement activity, and demographic trends over time. This information is a component of ongoing efforts to promote transparency and provide context for law enforcement within the community. For detailed guidance on interpreting arrest counts and demographic breakdowns, please refer to the [User Guide: Understanding the Arrests Demographic Datasets]. Why this Dataset is Organized this Way? The main arrests open data table includes key information from each arrest event, along with associated person and charge details in one place. This format is ideal for quick viewing and simple analysis. Providing this format supports a wide range of users, from casual data explorers to experienced analysts. Understanding the Arrests Open Data (main table / denormalized version) Each row in this dataset represents a single charge, which means a single arrest event may appear multiple times if multiple charges were filed. To determine the number of unique arrests, users should perform a distinct count of the rin field, which serves as the arrest incident identifier. Likewise: * To count unique arrestees, use a distinct count of the pin field (person identifier). * To count unique arresting officers, use a distinct count of the arrest_officer field. This structure enables users to explore charge-level detail while maintaining the ability to summarize demographic data by arrest event, arrestee, or officer as needed. Visit the [User Guide: Understanding the Arrests Demographic Datasets] for more details. [Data Dictionary] Additional Information Contact Email: [PD-DataRequest@tempe.gov] Contact Phone: N/A Link: N/A Data Source: Versaterm RMS Data Source Type: SQL Server Preparation Method: Automated process Publish Frequency: Daily Publish Method: Automatic
5.12 Cybersecurity (summary) - Archived

The National Institute of Standards and Technology (NIST) provides a Cybersecurity Framework (CSF) for benchmarking and measuring the maturity level of cybersecurity programs across all industries. The City uses this framework and toolset to measure and report on its internal cybersecurity program. The foundation for this measure is the Framework Core, a set of cybersecurity activities, desired outcomes, and applicable references that are common across critical infrastructure/industry sectors. These activities come from the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF) published standard, along with the information security and customer privacy controls it references (NIST 800 Series Special Publications). The Framework Core presents industry standards, guidelines, and practices in a manner that allows for communication of cybersecurity activities and outcomes across the organization from the executive level to the implementation/operations level. The Framework Core consists of five concurrent and continuous functions: identify, protect, detect, respond, and recover. When considered together, these functions provide a high-level, strategic view of the lifecycle of an organization’s management of cybersecurity risk. The Framework Core identifies underlying key categories and subcategories for each function, and matches them with example references, such as existing standards, guidelines, and practices for each subcategory. This page provides data for the Cybersecurity performance measure. Cybersecurity Framework cumulative score summary per fiscal year quarter (Performance Measure 5.12) The performance measure page is available at [5.12 Cybersecurity]. Additional Information Source: Maturity assessment / https://www.nist.gov/topics/cybersecurity Contact: Scott Campbell Contact E-Mail: Scott_Campbell@tempe.gov Data Source Type: Excel Preparation Method: The data is a summary of a detailed and confidential analysis of the city's cybersecurity program. Maturity scores of subcategories within NIST CFS are combined, averaged, and rolled up to a summary score for each major category. Publish Frequency: Annual Publish Method: Manual [Data Dictionary]