Improved Lobbyist Data
Edited 8/21/2017 to add the new Expenditures – Hosting dataset.
We have revamped the presentation of data about lobbyists on our Open Data Portal. People lobbying the City of Chicago are required to register with the Board of Ethics and file periodic reports through its Electronic Lobbyist Filing System (ELF), which began collecting data in 2012. The data structures are complex and previous attempts to recombine data about lobbyists, their employers, their clients, and their lobbying activity on behalf of these entities into tabular datasets ended up being difficult to understand.
In our new approach, we are publishing the data in a way that more closely matches the structures in the source system. Most of the datasets contain only a single type of information, with sufficient common IDs between the datasets for users to link them, as needed. The subjects of these datasets are:
- Compensation received by the lobbyists
- Contributions (political) made by the lobbyists
- Expenditures – Hosting
- Expenditures – Large ($250 or more, itemized)
- Expenditures – Small (under $250, summarized)
- Gifts made by lobbyists
- Lobbying Activity by lobbyists
There is one dataset that does combine multiple types of information. It links a lobbyist and his or her employer and clients. This dataset contains elements from the Lobbyist, Employers, and Clients datasets but has been combined to give a single view of information from all three in order to show the most central set of relationships in the data:
- Lobbyist, Employer, Client Combinations (each unique combination of the records from these three datasets)
Connections Between the Datasets
The new datasets have the indicated ID columns in common to allow for linking between datasets.
The older datasets are still present on the Data Portal. The Historical datasets are based on the predecessor system to ELF and contain data prior to 2012. The Deprecated datasets are the previous presentation of ELF data, beginning in 2012. (There is discussion of our general approach to dataset deprecation in this post on our developer blog.)