The main goal of this project is to integrate, extend, and apply our earlier NSF-funded efforts (CSSI Elements OAC-1931541 and RIDIR SBE-SMA-1539302) in cyber-infrastructure (CI) in order to (1) provide CI for political data production as well as creating our own novel political and social conflict data, such as event data. Endpoint of our integration is to create transformative, robust, and reliable science and engineering tools to benefit conflict research as well as other social and behavioral science applications. To this end, we use natural language processing techniques at cutting edge of scalable big data resources and language modeling. Event data in this context refers to a machine-coded description of someone doing something to someone else as extracted from news reports. We focus on political and social events about conflict and cooperation between governments, individuals, non?governmental organizations, rebel groups, and others. Data access and usability: • Our data along with other open event data are available through our API and R interface. • https://github.com/eventdata/UTDEventData • https://eventdata.utdallas.edu/ Event data extraction: • ConfliBERT: a domain-specific pre-trained language model for conflict and political violence [1]. • Available at github.com/eventdata/ConfliBERT • ConfliBERT Spanish and Arabic: extended ConfilBERT to multiple languages [2-3] • Extractive Question Answering (QA) in Political Conflict Research