Abstract Background: Cancer research is highly dependent on histopathology analysis for diagnosis, prognosis, and treatment. However, the majority of valuable histology data is stored in private archives on glass slides and local hard drives, and not shared like bioinformatics data. Lack of centrally-located data leads to repetitive, redundant research and makes it difficult for cancer researchers to work collaboratively by limiting widespread access and image sharing. Development of a virtual slide database on a scalable IT infrastructure will improve cancer histology data viewing and searching resulting in enhanced global scientific collaboration, allowing cancer to be fought cooperatively instead of individually. Design: The main repository for WizBase is a relational database powered by Amazon Web Services with online viewing, collaboration and long-term archiving of WSIs. We will also create ontology parameters and tagging approach using 3 types metadata: Type I, classification parameters, specimen information and experimental details captured at order submission; Type II, ontology terms and annotation added upon visualization of the slide by HistoWiz and slide owners; and Type III, crowd-sourced tags and collaborative comments not requiring formality or standardization. Results: We have developed a robust IT infrastructure allowing for viewing, tagging and searching of histology images. HistoWiz viewer is the first Cloud based viewer that allows users to instantly view their histology slides on any mobile device without the need to download any files, software or plugins. Furthermore, we have establish ontology parameters (such as metastasis, necrosis, neovascularization) for the classification and tagging of digital pathology cancer images, and slide metadata are captured during online order submission. Finally, through defined field and free text tagging of the slide metadata, users can search for slides meeting specific criteria. Searches based on similarity to a particular subject slide metadata allows ranking slide relevancy. The crowdsourced database currently has >10,000 histology slides and is growing at a rate of 300% per year. Conclusion: WizBaseTM is the first centralized Cloudbased WSI database for cancer histopathology with an image tagging web application to facilitate histology-driven data mining. WizBaseTM can be regarded as the scientific hybrid of a microscopy product with the viewing power of Google Earth combined with the search and crowdsourcing of Flickr. Citation Format: Ke Cheng. Development of a cloud-based histology database for collaborative cancer research. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Metastasis; 2015 Nov 30-Dec 3; Austin, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(7 Suppl):Abstract nr A64.