Pabulib

Pabulib is an open PArticipatory BUdgeting LIBrary. The aim of this website is to collect the participatory budgeting data from all over the world. In a companion paper we have introduced universal .pb data format in which we store all the files.

We hope that Pabulib will foster meaningful research on PB, in particularly by helping the computational social choice community to offer better aggregation methods to be used in real-world instances of PB.

The Pabulib project is maintained by the Jagiellonian Center for Quantitative Studies in Political Science and funded under the Polish Ministry of Science grant no. 0395/DLG/2018/10.

CBIP

The Jagiellonian Center for Quantitative Research in Political Science (CBIP) is an interdisciplinary research center focusing on the intersection of mathematics, computer science, and political science, ranging from classic and computational social choice theory, through mathematical modeling of elections and voting, to the application of machine learning and data mining algorithms to political science problems such as detection of gerrymandering or identification of voting patterns. The Center's research team includes mathematicians, computer scientists, political scientists, physicists, sociologists, lawyers, and geographers. In addition to research, the Center also develops and maintains database resources for researchers working on electoral systems, legislative studies, and political parties.

Authors

The Pabulib project was invented and is being developed by Dariusz Stolicki (a political scientist from the Jagiellonian University, Poland), Stanisław Szufa (a computer scientist from the Jagiellonian University, Poland) and by Nimrod Talmon (a computer scientist from the Ben-Gurion University, Israel).

Legal Disclaimer

Sharing of data sets including personally identifiable voter information may violate the laws of the country of origin or the European Union privacy law. Accordingly, we (1) ask the submitters to either remove all personally identifiable voter information before submission or to advise us of the manner in which such information may be contained in the dataset, and (2) reserve the right to unilaterally remove all personally identifiable voter information. By "personally identifiable voter information" we mean any information that may be used to ascertain the identity of individual voter with certainty and particularity.