The Algorithmic-Autoregulation (AA) Methodology and Software: a collective focus on self-transparency

TL;DR

The paper presents the Algorithmic-Autoregulation (AA) methodology and software, which enables technical communities to self-document and share their processes and efforts, promoting transparency and systematic accountability.

Contribution

It introduces the AA methodology and its software implementations, along with usage statistics, formal properties, and ontological frameworks for analysis and integration.

Findings

AA has been used since June 2011 by dozens of researchers and developers.

The methodology supports diverse tasks with various software gadgets.

Formal properties and ontologies facilitate comparison and integration of AA implementations.

Abstract

There are numerous efforts to achieve a lightweight and systematic account of what is done by a group and its individuals. The Algorithmic-Autoregulation (AA) is a special case, in which a technical community embraced the challenge of registering their own dedication for sharing processes, self-transparency, and documenting the efforts. AA is used since June/2011 by dozens of researchers and software developers, with the support of different software gadgets and for distinct tasks. This article describes these implementations and statistics of their usage including expected natural properties and ontological formalisms which eases comparative analysis and furthers integration.