Challenges and Opportunities for NSLP in Scientific Publishing – A Case Study

Abstract

Research software is not always meant to reach production-grade quality. The same requirements, for instance, regarding performance, security, or reliability that are imposed on professional software do not necessarily apply in the lab. However, recent years have seen an increased interest to bring cutting-edge research results into production. Specialized natural language processing, such as NSLP, is no exception. In this paper, we discuss three real-life challenges in scientific publishing as they relate to NSLP, and also highlight the potential NSLP has to offer in overcoming these challenges. Specifically, we identify issues related to the elicitation of metadata – particularly with respect to what we term the /metadata externality problem –, privacy and data protection laws, and software reliability. This is not a research paper; rather than introducing novel research results, our intention is to contribute to the academic discourse in the NSLP community by providing the perspective of a potential end-user.

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