Faced with the proliferation of scientific publications, scientific archives play a central role in helping users carry out bibliographic research. However, traditional keyword-based search services often fail to grasp the richness of the semantic associations between articles. In this paper, we present the methods, tools and services implemented in the ISSA project to tackle these issues. The project aims to (1) provide a generic, reusable pipeline for the analysis and processing of articles of an open scientific archive, (2) translate the result into a semantic index stored and represented as an RDF knowledge graph; (3) develop innovative search and visualization services that exploit this semantic index. The ISSA project is based on a use case that serves as proof of concept: Agritrop, CIRAD's open archive. Fully in line with the open science and FAIR dynamics, this work is available under an open license.