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A Language for Large-Scale Collaboration in Economics: A Streamlined Computational Representation of Financial Models

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  • Jorge Faleiro

Abstract

This paper introduces Sigma, a domain-specific computational representation for collaboration in large-scale for the field of economics. A computational representation is not a programming language or a software platform. A computational representation is a domain-specific representation system based on three specific elements: facets, contributions, and constraints of data. Facets are definable aspects that make up a subject or an object. Contributions are shareable and formal evidence, carrying specific properties, and produced as a result of a crowd-based scientific investigation. Constraints of data are restrictions defining domain-specific rules of association between entities and relationships. A computational representation serves as a layer of abstraction that is required in order to define domain-specific concepts in computers, in a way these concepts can be shared in a crowd for the purposes of a controlled scientific investigation in large-scale by crowds. Facets, contributions, and constraints of data are defined for any domain of knowledge by the application of a generic set of inputs, procedural steps, and products called a representational process. The application of this generic process to our domain of knowledge, the field of economics, produces Sigma. Sigma is described in this paper in terms of its three elements: facets (streaming, reactives, distribution, and simulation), contributions (financial models, processors, and endpoints), and constraints of data (configuration, execution, and simulation meta-model). Each element of the generic representational process and the Sigma computational representation is described and formalized in details.

Suggested Citation

  • Jorge Faleiro, 2018. "A Language for Large-Scale Collaboration in Economics: A Streamlined Computational Representation of Financial Models," Papers 1809.06471, arXiv.org.
    • Handle: RePEc:arx:papers:1809.06471
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    Cited by:

    1. Jorge Faleiro, 2018. "Enabling Scientific Crowds: The Theory of Enablers for Crowd-Based Scientific Investigation," Papers 1809.07195, arXiv.org.

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