You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Summarizing semantic graphs: a survey 
Chapter Title:  OWL 
1. Abstract of Cited Paper (BIB001):  We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.

Literature Review:
Semantic graphs considered in the literature for summarization sometimes go beyond the expressiveness of RDF, which comes with the simple RDF Schema ontology language. The standard by W3C for semantic graphs is the OWL [107,  family of dialects that builds on Description Logics (DLs) BIB001 . DLs are first-order logic languages that allow describing a certain application domain by means of concepts, denoting sets of objects, and roles, denoting binary relations between concept instances. DL dialects differ in the ontological constraints they allow expressing on complex concepts and roles, i.e., defined by DL formula. One of the most important issues in DLs is the trade-off between expressive power and computational complexity of reasoning with the constraints (consistency checking, query answering, etc.) The first flavor of OWL [107] consists of three dialects of increasing complexity: OWL-Lite, OWL-DL and OWL-Full. Unfortunately, very basic reasoning (concept satisfiability) in these dialects is highly intractable: ExpTime-complete in OWL-lite that corresponds to the SHIF D DL, NExpTimecomplete in OWL-DL that corresponds to the SHION D DL, and even undecidable in OWL-full. A second flavor of OWL  , a.k.a. OWL2, defines three new dialects, OWL2 EL based on the EL DL, OWL2 QL based on the DL-lite R DL and OWL2 RL which can be expressed using logical rules. These new dialects comes with PTIME complexity for most of the reasoning tasks. In particular, data management tasks (consistency checking, query answering, etc.) under OWL2 QL/DL-lite R ontologies have the same complexity as their counterparts in the relational database model BIB002 .