Minimal type inference for Linked Data consumers
We provide an introduction to the Web of Linked Data from the perspective of a Web developer who would like to build an application using Linked Data. We identify a weakness in the development stack, namely a lack of domain specific scripting languages for designing background processes that consume...
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sg-ntu-dr.10356-809742020-05-28T07:18:11Z Minimal type inference for Linked Data consumers Ciobanu, Gabriel Horne, Ross Sassone, Vladimiro School of Computer Engineering Linked Data Type systems Operational semantics We provide an introduction to the Web of Linked Data from the perspective of a Web developer who would like to build an application using Linked Data. We identify a weakness in the development stack, namely a lack of domain specific scripting languages for designing background processes that consume Linked Data. To address this weakness, we design a scripting language with a simple but appropriate type system. In our proposed architecture, some data is consumed from sources outside of the control of the system and some data is held locally. Stronger type assumptions can be made about the local data than about external data, hence our type system mixes static and dynamic typing. We prove that our type system is algorithmic; and can therefore be used for minimal type inference. We also prove subject reduction and type safety results, which justify our claim that our language is statically type checked and does not throw basic runtime type errors. Throughout, we relate our work to the W3C recommendations that drive Linked Data, so that our syntax is accessible to Web developers. Accepted version 2015-12-08T08:08:42Z 2019-12-06T14:18:40Z 2015-12-08T08:08:42Z 2019-12-06T14:18:40Z 2014 Journal Article Ciobanu, G., Horne, R., & Sassone, V. (2014). Minimal type inference for Linked Data consumers. Journal of Logical and Algebraic Methods in Programming, 84(4), 485-504. 2352-2208 https://hdl.handle.net/10356/80974 http://hdl.handle.net/10220/39004 10.1016/j.jlamp.2014.12.005 en Journal of Logical and Algebraic Methods in Programming © 2014 Elsevier Inc. This is the author created version of a work that has been peer reviewed and accepted for publication by Journal of Logical and Algebraic Methods in Programming, Elsevier Inc. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.jlamp.2014.12.005]. application/pdf |
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Linked Data Type systems Operational semantics Ciobanu, Gabriel Horne, Ross Sassone, Vladimiro Minimal type inference for Linked Data consumers |
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We provide an introduction to the Web of Linked Data from the perspective of a Web developer who would like to build an application using Linked Data. We identify a weakness in the development stack, namely a lack of domain specific scripting languages for designing background processes that consume Linked Data. To address this weakness, we design a scripting language with a simple but appropriate type system. In our proposed architecture, some data is consumed from sources outside of the control of the system and some data is held locally. Stronger type assumptions can be made about the local data than about external data, hence our type system mixes static and dynamic typing. We prove that our type system is algorithmic; and can therefore be used for minimal type inference. We also prove subject reduction and type safety results, which justify our claim that our language is statically type checked and does not throw basic runtime type errors. Throughout, we relate our work to the W3C recommendations that drive Linked Data, so that our syntax is accessible to Web developers. |
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School of Computer Engineering |
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School of Computer Engineering Ciobanu, Gabriel Horne, Ross Sassone, Vladimiro |
format |
Article |
author |
Ciobanu, Gabriel Horne, Ross Sassone, Vladimiro |
author_sort |
Ciobanu, Gabriel |
title |
Minimal type inference for Linked Data consumers |
title_short |
Minimal type inference for Linked Data consumers |
title_full |
Minimal type inference for Linked Data consumers |
title_fullStr |
Minimal type inference for Linked Data consumers |
title_full_unstemmed |
Minimal type inference for Linked Data consumers |
title_sort |
minimal type inference for linked data consumers |
publishDate |
2015 |
url |
https://hdl.handle.net/10356/80974 http://hdl.handle.net/10220/39004 |
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1681059525472288768 |