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JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases

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Abstract

The large volume and variety of data produced in the current Big Data era lead companies to seek solutions for the efficient data management. Within this context, NoSQL databases rise as a better alternative to the traditional relational databases, mainly in terms of scalability and availability of data. A usual feature of NoSQL databases is to be schemaless, i.e., they do not impose a schema or have a flexible schema. This is interesting for systems that deal with complex data, such as GIS. However, the lack of a schema becomes a problem when applications need to perform processes such as data validation, data integration, or data interoperability, as there is no pattern for schema representation in NoSQL databases. On the other hand, the JSON language stands out as a standard for representing and exchanging data in document NoSQL databases, and JSON Schema is a schema representation language for JSON documents that it is also leading to become a standard. However, it does not include spatial data types. From this limitation, this paper proposes an extension to JSON Schema, called JS4Geo, that allows the definition of schemas for geographic data. We demonstrate that JS4Geo is able to represent schemas of any NoSQL data model, as well as other standards for geographic data, like GML and KML. We also present a case study that shows how a data integration system can benefit of JS4Geo to define local schemas for geographic datasets and generate an integrated global schema.

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Notes

  1. https://github.com/geojson/schema

  2. More details about JSON and related standards are given in the next section.

  3. We assume JSON as the format for representing document instances given its acceptance by almost all NoSQL document DBMSs.

  4. https://www.json.org

  5. http://json-schema.org

  6. https://github.com/geojson/schema

  7. http://schemastore.org/json/

  8. N/A means Not Applicable.

  9. https://goessner.net/articles/JsonPath/

  10. http://www2.portoalegre.rs.gov.br/spm/

  11. http://datapoa.com.br/

  12. http://www.nosbairros.com.br/utilidade/delegacia-porto-alegres.htm

  13. http://www2.portoalegre.rs.gov.br/sms/default.php?p_secao=917

  14. https://www.qgis.org/en/site/

  15. https://en.wikipedia.org/wiki/Geohash

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Acknowledgements

This research was partially financed by the Instituto Federal Catarinense (IFC) and by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Brazil - Finance Code 001.

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  1. Instituto Federal Catarinense - IFC, Santa Catarina, Brazil

    Angelo A. Frozza

  2. Universidade Federal de Santa Catarina - UFSC, Florianópolis, Brazil

    Ronaldo dos S. Mello

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  1. Angelo A. Frozza
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Correspondence to Angelo A. Frozza.

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Frozza, A.A., Mello, R.d.S. JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases. Geoinformatica 24, 987–1019 (2020). https://doi.org/10.1007/s10707-020-00415-w

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