@inproceedings{63434,
  author       = {{Hoffmann, Max}},
  booktitle    = {{Proceedings of the Fourteenth Congress of the European Society for Research in Mathematics Education (CERME14)}},
  editor       = {{Bosch, Marianna and Bolondi, Giorgio and Carreira, Susana and Michael, Gaidoschik and Camilla, Spagnolo}},
  keywords     = {{hoffmann, reviewed, proceedings}},
  title        = {{{Using scriptwriting as a response format for interface tasks: Exemplary analyses in the context of symmetry}}},
  year         = {{2025}},
}

@inproceedings{29035,
  abstract     = {{The combination of the advantages of widely used relational databases and semantic technologies has attracted significant research over the past decade. In particular, mapping languages for the conversion of databases to RDF knowledge bases have been developed and standardized in the form of R2RML. In this article, we first review those mapping languages and then devise work towards a unified formal model for them. Based on this, we present the Sparqlification Mapping Language (SML), which provides an intuitive way to declare mappings based on SQL VIEWS and SPARQL construct queries. We show that SML has the same expressivity as R2RML by enumerating the language features and show the correspondences, and we outline how one syntax can be converted into the other. A conducted user study for this paper juxtaposing SML and R2RML provides evidence that SML is a more compact syntax which is easier to understand and read and thus lowers the barrier to offer SPARQL access to relational databases.}},
  author       = {{Stadler, Claus and Unbehauen, Joerg and Westphal, Patrick and Sherif, Mohamed and Lehmann, Jens}},
  booktitle    = {{Proceedings of the 8th Workshop on Linked Data on the Web (LDOW2015), Florence, Italy}},
  keywords     = {{2015 group\_aksw group\_mole mole stadler lehmann sherif simba dice sys:relevantFor:geoknow geoknow peer-reviewed MOLE westphal}},
  title        = {{{Simplified RDB2RDF Mapping}}},
  year         = {{2015}},
}

@inproceedings{29017,
  author       = {{Jay Le Grange, Jon and Lehmann, Jens and Athanasiou, Spiros and Garcia Rojas, Alejandra and Giannopoulos, Giorgos and Hladky, Daniel and Isele, Robert and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed and Stadler, Claus and Wauer, Matthias}},
  booktitle    = {{Proceedings of the Linking Geospatial Data Workshop}},
  keywords     = {{2014 group\_aksw group\_mole mole ngonga lehmann sherif topic\_Lifecycle sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:lod2 sys:relevantFor:geoknow geoknow lod lod2page peer-reviewed MOLE simba dice wauer stadler}},
  title        = {{{The GeoKnow Generator: Managing Geospatial Data in the Linked Data Web}}},
  year         = {{2014}},
}

@article{29036,
  abstract     = {{The improvement of public health is one of the main indicators for societal progress. Statistical data for monitoring public health is highly relevant for a number of sectors, such as research (e.g. in the life sciences or economy), policy making, health care, pharmaceutical industry, insurances etc. Such data is meanwhile available even on a global scale, e.g. in the Global Health Observatory (GHO) of the United Nations's World Health Organization (WHO). GHO comprises more than 50 different datasets, it covers all 198 WHO member countries and is updated as more recent or revised data becomes available or when there are changes to the methodology being used. However, this data is only accessible via complex spreadsheets and, therefore, queries over the 50 different datasets as well as combinations with other datasets are very tedious and require a significant amount of manual work. By making the data available as RDF, we lower the barrier for data re-use and integration. In this article, we describe the conversion and publication process as well as use cases, which can be implemented using the GHO data.}},
  author       = {{Zaveri, Amrapali and Lehmann, Jens and Auer, Sören and M. Hassan, Mofeed and Sherif, Mohamed and Martin, Michael}},
  journal      = {{Semantic Web Journal}},
  keywords     = {{2013 MOLE group\_aksw zaveri martin lehmann auer hassan sherif simba dice sys:relevantFor:infai sys:relevantFor:bis sys:relevantFor:lod2 lod2page peer-reviewed gho}},
  number       = {{3}},
  pages        = {{315–322}},
  title        = {{{Publishing and Interlinking the Global Health Observatory Dataset}}},
  volume       = {{Special Call for Linked Dataset descriptions}},
  year         = {{2013}},
}