The dblp database indexes meta data of more than 7.5 million publications in computer science and related fields. The primary goal of dblp is to create clean bibliographies for the 3.6 million authors of these publications. Author affiliations are a common feature of bibliographic data. However, using them in data curation comes with a set of challenges. The SmartER Affiliations project aims to make affiliation data a "first class citizen" in the curation process of dblp and similar databases. The goals of the project are to (1) locate and extract high quality affiliation data for scientific publications. (2) Integrate affiliation data into the curation processes of dblp and (3) make it available in the user interface for example as part of a search function. The experience gathered throughout the project will be useful for similar collections that plan to extend the use of affiliation data in their processes. All data collected with the tools designed in this project will be published under FAIR principles.

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Florian Reitz