“Dataset Search for Data Discovery, Augmentation and Explanation” with Juliana Freire, NYU
NYU CUSP's Research Seminar Series features leading voices in the growing field of urban informatics. Check out upcoming seminars: https://bit.ly/3rAfIW7
Recent years have seen an explosion in our ability to collect and catalog immense amounts of data about our environment, society, and populace. Moreover, with the push towards transparency and open data, scientists, governments, and organizations are increasingly making structured data available on the Web and in data lakes. Combined with advances in analytics and machine learning, the availability of such data should in theory allow us to make progress on many of our most important scientific and societal questions. However, this opportunity is often missed due to a central technical barrier: it is currently nearly impossible for domain experts to weed through the vast amount of available information to discover datasets that are needed for their specific application. While search engines have addressed the discovery problem for Web documents, there are many new challenges involved in supporting the discovery of structured data—from crawling the Web in search of datasets, to the need for dataset-oriented queries and new strategies to rank and display results. Juliana Freire, Professor of Computer Science and Data Science at NYU, will discuss these challenges and present our recent work in this area, including the Auctus dataset search engine and scalable techniques to support dataset discovery queries.