Bring the README.md up to date (ad-freiburg#992)

README.md

@@ -5,23 +5,19 @@
 [![Format check](https://github.com/ad-freiburg/qlever/actions/workflows/format-check.yml/badge.svg)](https://github.com/ad-freiburg/qlever/actions/workflows/format-check.yml)
 [![Test coverage](https://codecov.io/github/ad-freiburg/qlever/branch/master/graph/badge.svg?token=OHcEh02rW0)](https://codecov.io/github/ad-freiburg/qlever)
 
-QLever (pronounced "Clever") is a SPARQL engine that can efficiently index and query very large knowledge graphs with up to 100 billion triples on a single standard PC or server.
+QLever (pronounced "Clever") is a SPARQL engine that can efficiently index and query very large knowledge graphs with over 100 billion triples on a single standard PC or server.
 In particular, QLever is fast for queries that involve large intermediate or final results, which are notoriously hard for engines like Blazegraph or Virtuoso.
 QLever also supports search in text associated with the knowledge base, as well as SPARQL autocompletion.
 
-[Here are demos of QLever](http://qlever.cs.uni-freiburg.de) on a variety of large knowledge graphs, including the complete Wikidata, OpenStreetMap, PubChem, and DBLP.
-Those demos also feature QLever's context-sensitiv autocompletion, which makes SPARQL query construction so much easier. The datasets for Wikdiata and DBLP are updated automatically and hence always the latest versions (click on "Index Information").
+[Here are demos of QLever](http://qlever.cs.uni-freiburg.de) on a variety of large knowledge graphs, including the complete Wikidata, Wikimedia Commons, OpenStreetMap, UniProt, PubChem, and DBLP.
+Those demos also feature QLever's context-sensitive autocompletion, which makes SPARQL query construction so much easier. The knowledge graphs are updated regularly. Click on "Index Information" for a short description (with dates) and basic statistics.
 
-QLever was first described and evaluated in this [CIKM'17
-paper](http://ad-publications.informatik.uni-freiburg.de/CIKM_qlever_BB_2017.pdf).
-QLever has developed a lot since then.
-Qlever's autocompletion functionality and some other new features are described and evaluated in [this paper](https://ad-publications.cs.uni-freiburg.de/ARXIV_sparql_autocompletion_BKKKS_2021.pdf).
-If you use QLever in your work, please cite those papers.
-QLever supports standard SPARQL 1.1 constructs like:
-LIMIT, OFFSET, ORDER BY, GROUP BY, HAVING, COUNT, DISTINCT, SAMPLE, GROUP_CONCAT, FILTER, REGEX, LANG, OPTIONAL, UNION, MINUS, VALUES, BIND.
-Predicate paths and subqueries are also supported.
-The SERVICE keyword is not yet supported, but we are working on it.
-We aim at full SPARQL 1.1 support and we are almost there (except for SPARQL Update operations, which are a longer-term project).
+If you use QLever in your research work, please cite one of the following publications:
+our [CIKM'17 paper](https://ad-publications.informatik.uni-freiburg.de/CIKM_qlever_BB_2017.pdf) (combination of SPARQL and text search, with extensive evaluation),
+our [CIKM'22 paper](https://ad-publications.cs.uni-freiburg.de/CIKM_sparql_autocompletion_BKKKS_2022.pdf) (QLever's autocompletion, with extensive evaluation),
+our [2023 book chapter](https://ad-publications.cs.uni-freiburg.de/CHAPTER_knowledge_graphs_BKKK_2023.pdf) (survey of knowledge graphs and basics of QLever, with many example queries).
+
+QLever aims at full SPARQL 1.1 support and is almost there. In particular, a first version of SPARQL 1.1 Federated Query (SERVICE) is implemented since [PR #793](https://github.com/ad-freiburg/qlever/pull/793) and a proof of concept for SPARQL 1.1 Update is implemented since [PR #916](https://github.com/ad-freiburg/qlever/pull/916). If you find a bug in QLever or in one of our demos or if you are missing a feature, please [open an issue](https://github.com/ad-freiburg/qlever/issues).
 
 # Quickstart
 
@@ -32,7 +28,7 @@ which makes it very easy to get started and also helps to write your own `Qlever
 QLever via docker (which is the default setting), the script pulls the most recent docker image automatically and you
 don't have to download or compile the code.
 
-# Advanced feature, in-depth information, and older documentation
+If the `qlever` script does not work for you for whatever reason, have a look at the [Dockerfile for Ubuntu 22.04](https://github.com/ad-freiburg/qlever/blob/master/Dockerfile) or the [Dockerfiles for older Ubuntu versions](https://github.com/ad-freiburg/qlever/tree/master/Dockerfiles). The [source code of the qlever script](https://github.com/ad-freiburg/qlever-control/blob/main/qlever) also provides information on how to use QLever (in particular, note the functions `action_start` and `action_index`).
 
 An older (and not quite up-to-date anymore) step-by-step instruction can be found [here](docs/quickstart.md).
 QLever's [advanced features are described here](docs/advanced_features.md).