Data is everywhere, but not always accessible to everyone. Conventional data visualization tools and guidelines often assume a standard user, neglecting the neurodivergent needs of individuals with cognitive disabilities. These disabilities can create significant obstacles in data-driven reasoning, including difficulties in processing complex information, interpreting abstract concepts, and maintaining attention. This exclusion often results in ethical issues and barriers across various life domains, preventing individuals from living independent lives and fully participating in society. Since 2018, I have been dedicated to addressing these challenges by working with individuals with Intellectual and Developmental Disabilities (IDD), such as Down syndrome, Autism, and Cerebral Palsy, to enhance cognitive data accessibility. My research focuses on developing cognitively accessible visualizations designed to facilitate accessible, relatable, and personally meaningful interactions with data for individuals with diverse abilities. This dissertation asserts that conventional data visualization tools inadequately serve the neurodivergent population, particularly individuals with IDD. By developing and implementing cognitively accessible visualizations, my research aims to enhance data comprehension and interaction for cognitively diverse populations. I follow a three-step approach: (1) understanding data accessibility, (2) uncovering everyday data experiences, and (3) unlocking the neurodivergent potential for data authoring. Through this approach, the dissertation provides actionable insights and methodologies to democratize data access, fostering inclusivity and empowering individuals with IDD to effectively engage in data-driven conversations. Bridging the gap between data accessibility and the neurodivergent community, this dissertation aims to pave the way for more inclusive and equitable data interactions. By addressing the unique needs of individuals with cognitive disabilities, it establishes cognitive accessibility as an emerging field within visualization, emphasizing the necessity for inclusive design principles accommodating a wider range of cognitive abilities. The findings and methodologies presented lay a critical foundation for future research and practical applications, offering a roadmap for developing tools and techniques that make data more accessible to everyone. Additionally, insights from this research can inform policy and advocacy efforts aimed at promoting digital inclusivity and equity. Ultimately, this work contributes to the broader goal of creating a more just and inclusive society, where everyone benefits from the power of data and can make informed decisions. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]