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Add section "Use Cases" #14

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Add page describing datasets
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Renamed to `Use Case`, moved to first section. and revised
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10 changes: 0 additions & 10 deletions docs/demos.md
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2 changes: 1 addition & 1 deletion docs/index.md
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[Publications](publications.md): Publications on the various aspects and internals of QLever.

[Demos](demos.md): Links to public SPARQL endpoints running QLever.
[Uses Cases](use-cases.md): A selection of uses cases for QLever, many with public demos.

[FAQ](faq.md): Frequently asked questions.
120 changes: 0 additions & 120 deletions docs/qlever-control/datasets.md
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28 changes: 28 additions & 0 deletions docs/use-cases.md
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# Use Cases

QLever comes with a number of ready-to-use `Qleverfile`s for a variety of datasets. To get one of these `Qleverfile`s, run `qlever setup-config <name>`; for example `qlever setup-config wikidata`. Using that `Qleverfile`, you can then download the data, load it into QLever, and start a QLever server using simple `qlever` commands as described in the [quickstart](quickstart.md).

The following table provides an overview of the available `Qleverfile`s and the associated system requirements. The numbers measured on a machine with an AMD Ryzen 9 9950X processor (16 cores), 128 GB of RAM, and sufficient disk space. The disk consumption from QLever (excluding the dataset itself) during index building is slightly larger than the final index size (twice as much is always sufficient). No more RAM is needed to queries than for building the index. The RAM consumption at query time can be [limited in the settings](qleverfile.md#section-server).

| Dataset | Endpoint | Number of triples | Index size | RAM (Indexing) | Indexing time | Description |
| ----------------------------------- | ----------------------------------------------------------------------------------------- | ----------------- | ---------- | -------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `dblp` | [Official (QLever)](https://sparql.dblp.org/) | ~1.5 B | ~25 GB | ~20 GB | ~30 m | [DBLP](https://dblp.org/) is a computer science bibliography. This dataset contains the DBLP dataset with citations from [OpenCitations](https://opencitations.net/). |
| `dbpedia` | [Official](https://databus.dbpedia.org/sparql), [QLever Demo](https://qlever.dev/dbpedia) | ~845 M | - | - | ~20 m | The [DBpedia](https://databus.dbpedia.org/) dataset contains information extracted from the structured Wikipedia elements like the infoboxes. |
| `default` | | N/A | N/A | N/A | N/A | A minimal QLeverfile that can be used to build a custom configuration for your dataset. |
| `dnb` | [Official (QLever)](https://sparql.dnb.de/) | ~240 M | - | ~5 GB | ~5 m | The [German National Library (DNB)](https://www.dnb.de/EN/Home/home_node.html) is the central archival library for Germany. The dataset contains information on the publications in the DNB's inventory. |
| `fbeasy` | [QLever Demo](https://qlever.dev/fbeasy) | ~362 M | - | ~10 GB | ~10 m | FBEasy is a simplified and cleaned version of the [`freebase`](#freebase) dataset. |
| <a id="freebase"></a>`freebase` | [QLever Demo](https://qlever.dev/freebase) | ~3.1 B | - | ~20 GB | ~4 m | Freebase was a collaborative knowledge base, which became read-only in 2015, and was then superseded by Wikidata |
| `imdb` | [QLever Demo](https://qlever.dev/imdb) | ~382 M | - | ~5 GB | ~5 m | A dataset containing basic movie and ratings information from the film and series database [IMDb](https://www.imdb.com/). The dataset is available at <https://datasets.imdbws.com/>. |
| `ohm-planet` | [QLever Demo](https://qlever.dev/ohm-planet) | ~5.8 B | ~60 GB | ~10 GB | ~1 h | The [OpenHistoricalMap](https://www.openhistoricalmap.org/) is a OpenStreeMap like dataset of the world throughout history. The data modelling is similar to the [`osm-planet` dataset](#osm-planet). [`osm2rdf`](https://github.com/ad-freiburg/osm2rdf) is required to build the index. |
| `olympics` | [QLever Demo](https://qlever.dev/olympics) | ~1.8 M | ~20 MB | ~1 GB | ~10 s | A demo dataset with historic data on the olympic winter and summer games from Athens 1896 to Rio 2016. More information can be found in the [repository of this dataset](http://github.com/wallscope/olympics-rdf). |
| `orkg` | [QLever Demo](https://qlever.dev/orkg) | ~3 M | - | - | N/A | The [Open Research Knowledge Graph (ORKG)](https://orkg.org/) describes research papers mainly from biology and computer science. |
| `osm-country` | | N/A | N/A | N/A | N/A | A template for running an engine with [OpenStreetMap](https://www.openstreetmap.org/) data for a single country. The data model is identical to the [`osm-planet`](#osm-planet) dataset. [`osm2rdf`](https://github.com/ad-freiburg/osm2rdf) is required to build the index.Adjust `CONTINENT` and `COUNTRY` to your needs. All available continents and countries can be found at [Geofabrik](https://download.geofabrik.de/). |
| <a id="osm-planet"></a>`osm-planet` | [QLever Demo](https://qlever.dev/osm-planet) | ~204 B | ~1.5 TB | ~60 GB | ~20 h | [OpenStreetMap](https://www.openstreetmap.org/) is an open-source map. This is the complete OpenStreetMap planet dataset including nodes, ways and relations. The geometries can be queried using [GeoSPARQL](geosparql.md). Uses an RDF dump of the dataset from <https://osm2rdf.cs.uni-freiburg.de> which was converted using `osm2rdf`. |
| `osm-planet-from-pbf` | [QLever Demo](https://qlever.dev/osm-planet) | ~204 B | ~2.5 TB | ~60 GB | ~40 h | The [`osm-planet`](#osm-planet) dataset with the difference that the data ist generated directly from the latest dump which requires `osm2rdf`. |
| `pubchem` | [QLever Demo](https://qlever.dev/pubchem) | ~26 B | ~350 GB | ~20 GB | ~6 h | PubChem is a database of chemical data. |
| `scientists` | [QLever Demo](https://qlever.dev/scientists) | ~370 M | - | - | ~20 s | Scientists and associated triples and text (used for QLever-internal testing) |
| `uniprot` | [QLever Demo](https://qlever.dev/uniprot) | ~240 B | ~ 3 TB | ~60 GB | ~40 h | [UniProt](https://www.uniprot.org/) is a database of proteins. |
| `vvz` | | | | | | This dataset is used internally and **not publicly available**. The dataset contains information on the teaching (lectures, lecturers, rooms, examination regulations) at the faculty of engineering at the University Freiburg. In the future this dataset will power the [faculties course catalog](https://vvz.tf.uni-freiburg.de). |
| <a id="wikidata"></a>`wikidata` | [QLever Demo](https://qlever.dev/wikidata) | ~ 21 B | ~500 GB | ~20 GB | ~5 h | [Wikidata](https://www.wikidata.org) is a collaborative knowledge base (think Wikipedia for structured data) under the umbrella of the Wikimedia fundation. |
| `wikipathways` | | - | - | - | ~20 s | [Wikipathways](https://www.wikipathways.org/) is a database of biological pathways. The latest snapshot will be used by default. Set `RELEASE` to a snapshot from <https://data.wikipathways.org/> to used a different snapshot. |
| `yago-4` | [QLever Demo](https://qlever.dev/yago-4) | ~2.5 B | - | ~10 GB | ~4 h | [Yago-4](https://yago-knowledge.org/) is built on [Wikidata](#wikidata) but simplifies the data. The changes to Wikidata include huma-readable identifiers and different classes and properties. |
3 changes: 1 addition & 2 deletions mkdocs.yml
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Expand Up @@ -9,7 +9,7 @@ nav:
- Benchmarks: benchmarks.md
- Compliance: compliance.md
- Publications: publications.md
- Demos: demos.md
- Use Cases: use-cases.md
- FAQ: faq.md
- Troubleshooting: troubleshooting.md
# - Getting started:
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- Update: update.md
- Materialized Views: materialized-views.md
- Rebuild index: rebuild-index.md
# - Datasets: qlever-control/datasets.md

repo_url: https://github.com/ad-freiburg/qlever
edit_uri: https://github.com/qlever-dev/qlever-docs/edit/master/docs
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