Today’s scholarly, born-digital articles are no longer best represented by single documents but rather consist of a narrative connecting a collection of research components. They contain references to other papers, data products, people, institutions, funding sources, among others. Since the whole of the products referenced by a scholarly article forms the best representation of the science discussed in the article, having a proper coverage of these sources will help in properly representing different aspects and stages of research life cycles. Just capturing citations to other scholarly publications would not only leave out important information, it would also omit proper attribution to researchers who contribute as authors of non-traditional research products. The ADS has implemented a workflow for capturing software citations, the concept of which was presented at LISA VIII (Muench et al, 2017); this workflow allows the detection and ingest of citations to software products used in scholarly publications (Henneken, 2017). Since both data and software citations are crucial for the transparency of research results and for the transmission of credit, the ADS will implement indexing of high-level data products, in particular those published by NASA Archives, and track their citations. We will conclude by speculating how additional text mining and curation efforts can be used to further link the literature to additional resources mentioned in the papers.