Providing machines with the capability of exploring knowledge graphs and answering natural language questions has been an active area of research over the past decade. In this direction translating natural language questions to formal queries has been one of the key approaches. To advance the research area, several datasets like WebQuestions, QALD and LCQuAD have been published in the past. The biggest data set available for complex questions (LCQuAD) over knowledge graphs contains five thousand questions. We now provide LC-QuAD 2.0 (Large-Scale Complex Question Answering Dataset) with 30,000 questions, their paraphrases and their corresponding SPARQL queries. LC-QuAD 2.0 is compatible with both Wikidata and DBpedia 2018 knowledge graphs. In this article, we explain how the dataset was created and the variety of questions available with examples. We further provide a statistical analysis of the dataset. Resource Type: Dataset Website and documentation: http://lc-quad.sda.tech/ Permanent URL: https://figshare.com/projects/LCQuAD_2_0/62270.