As a mandate of the New Orleans City Data Policy - Executive Order 16-01 & Policy Memorandum 135, we are taking an inventory of all City datasets. This on-going inventory process will help us to categorize and identify data that could be made publicly available. This process also assists our ability to work cross-departmentally and increases our resilience. Why is the data inventory important? • Stimulate new ideas and services. By publishing a data inventory, city departments may help to stimulate new and innovative ideas from the community. • Increase internal sharing and resilience. A data inventory can also help us access information from other departments that we need to improve service delivery and resilience planning. • Enabling better and more up-to-date processes. The process of publishing a data inventory will help us to realize the constraints of current City technology and processes, and then plan for future improvements. • Changing how we use data. A data inventory can help empower us to change how we use, share and consume our data externally and internally, ultimately transforming data into better services for citizens and fostering continuous improvement.
This dataset has the following 28 columns:
Column Name | API Column Name | Data Type | Sample Values |
---|---|---|---|
Department | department | text | Information Technology and Innovation Sanitation Health Department Revenue, Bureau of City Planning Commission view top 100 |
Dataset | dataset | text | Ranger Inspections Tire Shops Ranger Inspections Collection/Hauling Costs Ranger Signs Removed Garbage Collection Totals view top 100 |
Description | description | text | Removal of any illegal sign on the public right-of-way Inspections authorized by approved individuals that is conducted on a daily basis to ensure residents and business owners are in compliance with city or state codes Illegal Dumping of Debris Removed from the Public Right of Way Solid waste collection cost per unit Total curbside collection solid waste household count by area view top 100 |
Data steward | data_steward | text | Andrew Joseph Romy Samuel Chantrice Banks Sarah Babcock Kyle Homan view top 100 |
Data Source | data_source | text | Excel RCS LAMA excel n/a view top 100 |
Start Date | start_date | text | 2012 2011 2015 2009 Excel view top 100 |
End Date | end_date | text | current Current Continuous CONTINUOUS 2016 view top 100 |
Geographic granularity | geographic_granularity | text | Not applicable Street address Parcel (block/lot) Other Latitude/longitude view top 100 |
Frequency of Data Change | frequency_of_data_change | text | Continuous Monthly Not updated (historical only) Daily Weekly view top 100 |
Data source format | data_source_format | text | Excel SQL SQL Database excel Monthly view top 100 |
Is Published? | is_published | checkbox | false true view top 100 |
Open Data Link | open_data_link | url | {"url":"https://data.nola.gov/d/u6yx-v2tw"} {"url":"https://nola.gov/performance-and-accountability/archive/"} {"url":"https://data.nola.gov/d/62d3-pst8"} {"url":"https://data.nola.gov/City-Administration/311-Calls-2012-Present-/3iz8-nghx"} {"url":"https://nola.gov/city-planning/major-studies-and-projects/2015-short-term-rental-study/"} view top 100 |
Completeness | completeness | number | 3 2 1 0 view top 100 |
Accuracy | accuracy | number | 3 2 1 0 view top 100 |
Real-time Data Updates | real_time_data_updates | number | 2 3 1 view top 100 |
Data Quality Score | data_quality_score | number | 9 6 8 7 5 view top 100 |
Data Quality Grade | data_quality_grade | number | 100 88.89 66.67 77.78 55.56 view top 100 |
Data Classification | data_classification | number | 3 2 1 view top 100 |
Interest (Perceived Value) Level | interest_perceived_value_level | number | 2 3 1 0 view top 100 |
Supports City Program or Project (e.g. Workforce Development, Equity) | supports_city_program_or_project_e_g_workforce_development_equity | number | 1 3 2 0 view top 100 |
Increases gov't transparency & accountability | increases_gov_t_transparency_accountability | number | 3 2 1 0 view top 100 |
Open Data Score | open_data_score | number | 11 8 10 9 7 view top 100 |
Open Data Grade | open_data_grade | number | 91.67 66.67 83.33 75 58.33 view top 100 |
Automated | automated | number | 2 3 1 0 view top 100 |
Delivery Cost | delivery_cost | number | 2 3 1 0 view top 100 |
Maintenance Cost | maintenance_cost | number | 3 2 1 0 view top 100 |
Cost Score | cost_score | number | 6 9 7 8 5 view top 100 |
Cost Grade | cost_grade | number | 100 66.67 77.78 88.89 55.56 view top 100 |