4,243 research outputs found
Including widespread geometry formats in semantic graphs using RDF literals
The exchange of building data involves both geometric and non-geometric data. A promising Linked Data approach is to embed data from existing geometry formats inside Resource Description Framework (RDF) literals. Based on a study of relevant specifications and related work, this toolset-independent approach was found suitable for the exchange of geometric construction data. To implement the approach in practice, the File Ontology for Geometry formats (FOG) and accompanying modelling method is developed. In a proof-of-concept web application that uses FOG, is demonstrated how geometry descriptions of different existing formats are automatically recognised and parsed
Reasoning about modular datatypes with Mendler induction
In functional programming, datatypes a la carte provide a convenient modular
representation of recursive datatypes, based on their initial algebra
semantics. Unfortunately it is highly challenging to implement this technique
in proof assistants that are based on type theory, like Coq. The reason is that
it involves type definitions, such as those of type-level fixpoint operators,
that are not strictly positive. The known work-around of impredicative
encodings is problematic, insofar as it impedes conventional inductive
reasoning. Weak induction principles can be used instead, but they considerably
complicate proofs.
This paper proposes a novel and simpler technique to reason inductively about
impredicative encodings, based on Mendler-style induction. This technique
involves dispensing with dependent induction, ensuring that datatypes can be
lifted to predicates and relying on relational formulations. A case study on
proving subject reduction for structural operational semantics illustrates that
the approach enables modular proofs, and that these proofs are essentially
similar to conventional ones.Comment: In Proceedings FICS 2015, arXiv:1509.0282
Combining link and content-based information in a Bayesian inference model for entity search
An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework. A flexible query model is supported capable to reason with the availability of simple semantics in querie
What Does Aspect-Oriented Programming Mean for Functional Programmers?
Aspect-Oriented Programming (AOP) aims at modularising crosscutting concerns that show up in software. The success of AOP has been almost viral and nearly all areas in Software Engineering and Programming Languages have become "infected" by the AOP bug in one way or another. Interestingly the functional programming community (and, in particular, the pure functional programming community) seems to be resistant to the pandemic. The goal of this paper is to debate the possible causes of the functional programming community's resistance and to raise awareness and interest by showcasing the benefits that could be gained from having a functional AOP language. At the same time, we identify the main challenges and explore the possible design-space
Compensation methods to support cooperative applications: A case study in automated verification of schema requirements for an advanced transaction model
Compensation plays an important role in advanced transaction models, cooperative work and workflow systems. A schema designer is typically required to supply for each transaction another transaction to semantically undo the effects of . Little attention has been paid to the verification of the desirable properties of such operations, however. This paper demonstrates the use of a higher-order logic theorem prover for verifying that compensating transactions return a database to its original state. It is shown how an OODB schema is translated to the language of the theorem prover so that proofs can be performed on the compensating transactions
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