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Research in conceptual modeling is today undertaken in a large number of fields. We describe the results from a bibliometric analysis of major outlets for conceptual modeling research for investigating the evolution of research topics. As a basis for the study we used the openly accessible DBLP dataset which we enriched with data from related publisher's websites and databases. Besides a descriptive analysis of the publication data, we conducted a content-based analysis of more than 3.200 papers using Latent Dirichlet Allocation. This permits to gain insights into the past trends in conceptual modeling research and derive future prospects for the community.

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The creation of blockchain-based software applications requires today considerable technical knowledge, particularly in software design and programming. This is regarded as a major barrier in adopting this technology in business and making it accessible to a wider audience. As a solution, low-code and no-code approaches have been proposed that require only little or no programming knowledge for creating full-fledged software applications. In this paper we extend a review of academic approaches from the discipline of model-driven engineering as well as industrial low-code and no-code development platforms for blockchains. This includes a content-based, computational analysis of relevant academic papers and the derivation of major topics. In addition, the topics were manually evaluated and refined. Based on these analyses we discuss the spectrum of approaches in this field and derive opportunities for further research.