Skip to content
#generative ai Open access

Quantifying the Digital Heritage: A UNESCO-Inspired Value Index for Software Archives

Oct 2026 · ACM/IEEE Joint Conference on Digital Libraries · 2 references
Digital and Traditional Archives Management

Abstract

The Software Heritage (SWH) archive pursues the monumental mission of preserving the world’s software source code. However, the advent of generative AI has triggered an AI Code Explosion, exponentially accelerating the production of synthesized code and leading to severe storage capacity challenges. As preserving the entirety of global source code indefinitely presents an increasing physical and economic challenge for decentralized mirror servers, complementary strategies for archival prioritization become a valuable consideration. This poster introduces the Universal Value Index (UVI), a highly scalable, graph-topological heuristic model designed to quantify the “Outstanding Universal Value” of software repositories to assist in decentralized capacity planning. Inspired by established UNESCO World Heritage criteria, the UVI evaluates repositories across four dimensions: Impact, Time, Rarity, and Quality, alongside specific penalizations for redundant forks and data bloat. While determining objective value is intrinsically challenging, our preliminary goal is to provide a consistent and transparent first-step prioritization for archiving. By offering a mathematical framework mapped to cultural heritage standards, the UVI enables digital archivists to make scalable triage decisions to help secure critical digital infrastructure.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.