AndreaBozzo/ceres-open-data-index huggingface dataset:
Participation in Workforce Development Programs

This Indicator measures the percent of the unemployed population (ages 16 and up) in Oakland by race/ethnicity who did not participate in the City of Oakland’s Workforce Development program between 7/1/2016 and 6/30/2017. The percent that did participate for each race/ethnicity is calculated by dividing number of participants of that race/ethnicity by the number of unemployed people in the labor force in Oakland of that race/ethnicity. Percent that did not participate is 100% minus the percent that did participate. NOTE: Participation is not the most meaningful metric, but was the data available. In the future, we hope to replace this with a measurement of exit outcomes for participants by race/ethnicity (i.e., did participants successfully find jobs?).
Park Quality

This Indicator measures overall ratings for Oakland parks and compares average scores by City Council District. The overall ratings were based on an annual survey that assigned parks letter grades (A through F), which corresponded to scores (A=4, B=3, C=2, D=1 and F=0). In addition to Council District scores, the scores for parks surrounding Lake Merritt were reported as an average Lakeside score. The survey also included questions about greenery, amenities, recreation areas, and homeless encampments. For a map of the City Council Districts, see here: http://www2.oaklandnet.com/oakca1/groups/ceda/documents/image/oak044524.pdf.
Overcrowding

This Indicator measures the likelihood of individuals living in overcrowded housing, which is defined as housing units that have more than 1.5 people per room. Persons-per-room is the most common measure for overcrowding in housing, and 1.5 is a widely accepted threshold above which there are impacts on health and personal safety. (Source: https://www.huduser.gov/publications/pdf/measuring_overcrowding_in_hsg.pdf)
Teacher Experience

The measurement is percent of teachers who were paid on salary steps 1-5 at OUSD schools (data from charters and private schools were not available). Salary steps are a proxy for teaching experience, as teachers move one step up the salary schedule for each year of teaching. In theory, teachers on salary steps 1-5 have between 1-5 years of teaching experience (not just in OUSD, but anywhere). However, it is important to note that salary steps are just a proxy and not always exactly equal to years of teaching experience. Percents are then calculated at the school level by dividing the number of teachers on salary steps 1-5 by the total number of teachers at that school. Schools are placed into groups based on the racial and ethnic breakdown of their student population (see note below data table for full explanation of grouping). Average percent of teachers on salary steps 1-5 is then calculated for each group of schools.
OldIndust_LandUse

Summary: This layer was created to depict industrial land areas present in 1968. The layer is intended to contribute to a larger mapping and modeling effort designed to spatially depict land areas that may be sources of Polychlorinated Biphenyls (PCBs) or mercury in the San Francisco Bay Area. The land areas are termed “old industrial” due to their presence prior to roughly 1970, the timeframe when PCB production in the U.S. ceased. Old industrial land parcels in Alameda, Contra Costa, San Mateo, Santa Clara and Solano counties are depicted. Parcels in the datalayer are defined via the most currently available assessor’s parcel data for each county.
Oakland Slow Streets Program

Last updated July 8, 2020. This dataset includes street segments included in the City of Oakland Slow Streets Program. This program started with a pilot effort launching Saturday, April 11th with "soft closures" including signage, traffic cones and barricades. It began with candidates streets identified as existing or proposed neighborhood bike routes in Oakland's Bike Plan and later inclueded other streets. More information at https://www.oaklandca.gov/projects/oakland-slow-streets.
Oakland Limited Public Financing (LPF) Funding Totals by Candidate

The dataset contains records of Limited Public Financing (LPF) funding provided to candidates in Oakland -- summarizing the distribution of LPF funds. Each row represents an individual candidate's data, encompassing the election year/cycle, election type (general or special), the office sought (e.g., City Council - District 1), the candidate's name, the total amount of LPF funding received, the election outcome (whether the candidate won or not), and whether the candidate was an incumbent or challenger. The data is current as of the last modified date on this dataset. For more information about the Limited Public Financing Program, please visit our website.
Oakland Bikeway Signage

To download a projected shapefile of this dataset, please click "Download Projected Shapefile: Oakland Bikeway Signage" under "Attachments" below. Bicycle wayfinding, regulatory, warning, and other traffic signs focused on bicycle travel and bicyclists. Data included: location (street and cross street), sign type/s (MUTCD designation), sign messaging (where applicable), and installation instructions. This data includes existing signs, and a small number of proposed sign locations. Data is current through December 31, 2025. This dataset is updated twice annually in January and July.
Oakland Bike Parking

To download a projected shapefile of this dataset, please click "Download Projected Shapefile: Oakland Bike Parking" under "Attachments" below. This feature class includes data on publicly-accessible bicycle parking known to be installed in Oakland. Most of the bike racks were installed by the City of Oakland on public sidewalks. The types of bike parking reflected include bike racks on sidewalks, in the street (as part of bike parking corrals or parklets), in plazas, and garages; publicly accessible electronic bicycle lockers (mostly installed and owned by BART), and BART bike stations. This data reflects parking installed as of December 31, 2025. This dataset is updated twice annually in January and July.
Oakland Bike Wayfinding Projects

To download a projected shapefile of this dataset, please click "Download Projected Shapefile: Oakland Bike Wayfinding Projects" under "Attachments" below. This data includes the status of projects to implement Oakland's bicycle wayfinding sign system; http://www2.oaklandnet.com/oakca1/groups/pwa/documents/report/oak025118.pdf. Projects are constructed by corridor. Additional corridors from the update of Oakland's bicycle plan (July 2019) have not yet been included. Corridor projects prior to 2008 which include a different sign type are not shown on this map. Data current through December 31, 2025.
Juvenile Felony Arrests

This Indicator measures the rate of felony arrests of juveniles by race/ethnicity adjusted for population. This Indicator is measured for Oakland. Rate is calculated as the number of juvenile felony arrests per 100,000 people of each race/ethnicity that are under 18 years of age. To determine the number of juveniles of each race/ethnicity in Oakland, we took the population by race/ethnicity for all ages and multiplied by the percent of Oakland’s population that is under 18 (19.67%). This approach was necessary due to the lack of exact data available on the under 18 population in Oakland by race/ethnicity.
International BRT Parking and Curb Inventory

Fehr & Peers conducted a parking inventory and occupancy study in Oakland to support the ongoing International BRT project. The study area consisted of block faces within 1,500 feet of International Boulevard between 1st Avenue and Durant Avenue, a 6.8 mile-long corridor. Inventory and occupancy data was collected for over 2,500 block faces in February of 2018 between 11:00 AM and 3:00 PM. Block faces were selected for inclusion in the study if any portion of the block face was within 1,500 feet of International Boulevard between 1st Avenue and Durant Avenue. The total length of available parking on each block was collected for blocks with parallel parking, and a number of spaces was collected for those with angled or perpendicular parking. Spaces were further differentiated by metered, unmarked regular, commercial loading, passenger loading, and accessible spaces. Private access or otherwise reserved spaces were not included in the study. Data validation efforts included additional field visits to ground-truth the inventory data and ensure that the observed occupancies were typical, as well as comparisons of the inventory data to block face lengths to identify data entry errors. Certain block faces with identified data entry or collection errors were re-collected in subsequent field visits in March of 2018.
Important_Bird_Areas_2014

The objective of this project was to digitally map the boundaries of Audubon California's Important Bird Areas (IBA). Existing Important Bird Areas identify critical terrestrial and inland water habitats for avifauna, in particular, habitat that supports rare, threatened or endangered birds and/or exceptionally large congregations of shorebirds and/or waterfowl. The digitization of Important Bird Areas represents an important first step in conservation planning of these critical habitats using GIS. As of October 2007, a draft layer of all 148 Important Bird Areas in California was completed. Currently, a review is in progress with Audubon Chapters and local experts, with a final version completed by Nov. 1, 2008. The final map and data will be released to the public in November, 2008.
High School Readiness

The measurement is percent of students by race/ethnicity who are not high school ready by the end of 8th grade. High school readiness is calculated by OUSD. A student is considered high school ready when all of the following have been met at the end of 8th grade: 1) Total weighted GPA of 2.5 of better, 2) School Attendance 96% or better, 3) No “Ds” or “Fs” in their core English and Math course grades in 8th grade, 4) No suspensions in 8th grade.
High School On-Time Completion

This Indicator measures the percent of students who are still enrolled in high school after four years. Data is also provided on percent who graduated/completed high school within four years and percent who dropped out. The most recent year of OUSD graduation data is from 2015-16, so the cohort began 9th grade in 2012-13. Students who leave OUSD (but not from dropping out) are removed from the cohort, and students who enroll after 9th grade are added. GED completion and Special Ed Certification are included as types of completion.
Lobbyist Activity - Political Contributions (Schedule D)

This dataset includes contributions to elected officials and candidates for City office solicited by lobbyists listed in Schedule D of the Quarterly Lobbyist Activity Reports submitted to the City of Oakland. The dataset only includes data from reports submitted electronically. The data is current as of the last modified date on this dataset. To see complete reports visit the Public Lobbyist Dashboard and Data Portal at: https://apps.oaklandca.gov/pec/Lobbyist_Dashboard.aspx
Lobbyist Activity - Contacts with Public Officials (Schedule A)

This dataset includes contacts with City Officials by lobbyists to influence a governmental (municipal) decision on behalf of a client or employer listed in Schedule A of the Quarterly Lobbyist Activity Reports submitted to the City of Oakland. The dataset only includes data from reports submitted electronically. The data is current as of the last modified date on this dataset. To see complete reports visit the Public Lobbyist Dashboard and Data Portal at: https://apps.oaklandca.gov/pec/Lobbyist_Dashboard.aspx
Living Wage

This Indicator measures the hourly wage for all workers ages 16 and older and compares it to the 2016 Oakland living wage ($14.86 per hour). Hourly wages are calculated by dividing the total person’s earnings by the product of the weeks worked and the usual hours worked per week during the past 12 months. The weeks worked variable was set to the midpoint of the interval included in the ACS data. Only workers with non-zero earnings, who were not self- employed or unpaid family workers, and who were at work or had a job but were not at work last week were included in the analysis. (Source for methodology: http://laborcenter.berkeley.edu/pdf/2014/chartbook-data-and-methods.pdf)
Employment in High Wage Industries

This Indicator is measured by the percent of employed individuals who are not employed in industries with a mean annual wage of at least $80,000. In 2016, these industries included management occupations; legal occupations; healthcare practitioners and technical occupations; computer and mathematical occupations; architecture and engineering occupations; life, physical, and social science occupations; and business and financial operations occupations. (Source: Occupational Employment Statistics, CA Employment Development Department https://data.edd.ca.gov/Wages/Occupational-Employment- Statistics-OES-/pwxn-y2g5)
Linked Learning Pathway Enrollment

The measurement is percent of OUSD students (in Grades 10, 11, and 12) by race/ethnicity who are not enrolled in a Linked Learning Pathway. According to OUSD, Linked Learning is a successful approach to education based on the idea that students work harder and dream bigger if their education is relevant to them. These pathways, also known as college and career pathways, are a set of high school courses and work-based learning experiences such as internships that link academic learning to real world careers and college majors.
CrimeWatch Maps Past 90-Days

The Oakland Police Department provides crime data to the public through the City of Oakland's Crime Watch web site. This site presents the data in a geographic format, which allows users of the information to produce maps and/or reports. The file that you are about to electronically download, copy, or otherwise retrieve by other means is a tabular representation of the same data without maps or reporting capabilities. Be advised that the exact address of each crime has been substituted with the block address to protect the privacy of the victim. Please note: This Crime data are captured from reports filed with the police Department. There may be delays in data due to data processing, incident reporting or maybe technical in nature. Please allow up to 90 days from the end of each month for the data to be completely processed. For example, if you want to retrieve the full data set for the month of March, you will need to generate your report on or after June 30th. (A full 90 days after March 31st)
CrimeWatch Data

A full dataset of CrimeWatch data. The Oakland Police Department provides crime data to the public through the City of Oakland's Crime Watch web site. This site presents the data in a geographic format, which allows users of the information to produce maps and/or reports. The file that you are about to electronically download, copy, or otherwise retrieve by other means is a tabular representation of the same data without maps or reporting capabilities. Be advised that the exact address of each crime has been substituted with the block address to protect the privacy of the victim. Please note: This Crime data are captured from reports filed with the police Department. There may be delays in data due to data processing, incident reporting or maybe technical in nature. Please allow up to 90 days from the end of each month for the data to be completely processed. For example, if you want to retrieve the full data set for the month of March, you will need to generate your report on or after June 30th. (A full 90 days after March 31st)
Contracts Awarding

This Indicator measures the percent by race/ethnicity of Prime contractors for construction and professional services contracts who received under $100,000. Additional data is provided on the average amount received by these contractors. Data is from fiscal year 2015-16 and the date used to assign contracts to a fiscal year is the date that the compliance analysis was completed, or the review date. The dollar amounts represent the initial award; any negotiated bid amounts or change orders are not taken into account. The initial award is adjusted to how much of the total contract went to the Prime as opposed to Subprime contractors.
Equity Indicator Scores

The Indicators chosen represent the best proxies we could find for the complex disparity themes we set out to measure. The following criteria were used to determining the indicators included in each of the topics in the final framework: 1. Data is available, high quality, and from a reliable source. 2. We will be able to calculate change over time (i.e., data is updated and accessible on an annual basis and changes from year to year can be meaningfully interpreted). 3. There is a strong causal model for why this Indicator matters (i.e., we understand the context behind the Indicator and how disparities affect people). 4. The data accurately represents the impact of inequity on people’s lives (e.g., not measuring quantity when what matters is quality).
Equal Access Accommodations

The equal access accommodations Indicator is measured by comparing the percent of public contact position (PCP) employees who speak Spanish to the percent of Spanish speakers who have limited English proficiency (LEP) citywide. The Equal Access to Services Ordinance includes a requirement for City departments to offer bilingual services based on citywide demographics. In FY2016-2017, the two languages required by the ordinance were Spanish and Chinese. We chose to measure Spanish-speaking PCP employees for this Indicator because Spanish speakers comprise a larger proportion of the population.
Chronic Disease Preventable Hospitalizations

This Indicator measures the age-adjusted rate of chronic diseases preventable hospitalizations. “Preventable hospitalizations” are inpatient hospital stays that could have been avoided with improved access to and quality of outpatient care. They are measured by prevention quality indicators (PQIs). PQI #92, the chronic composite, is a summary measure which captures preventable hospitalizations from diabetes-related, respiratory-related and circulatory system-related preventable hospitalizations for adults, such as uncontrolled diabetes, asthma, and heart failure.(Source:http://www.healthyalamedacounty.org/indicators/index/view?indicatorId=2480&locale Id=238) This Indicator compares zip codes in which more than 60% of the population is non-White to those in which more than 60% of the population is White. The third category of zip codes is those in which the population is racially and ethnically mixed. Data is from 2013 through the third quarter of 2015.