Embarking on a PhD: Introducing the Multi Search Aggregator

I’m delighted to share an update regarding my doctoral research journey, which is now progressing at Universitat de Vic (ELISAVA Research group) & SUPSI . Following the formalisation of my research plan, I’ve been focusing on developing a tool designed to streamline a crucial aspect of academic inquiry: the systematic literature review. To that end, I’m pleased to introduce the Multi Search Aggregator (MSA), a Python-based tool created to simplify and expedite multi-search processes across various platforms. Currently supporting Google, DuckDuckGo, and Zenodo, with further integration of resources such as Google Scholar planned for future development, MSA is intended to be an invaluable asset for researchers undertaking comprehensive literature reviews. The systematic literature review demands meticulousness and efficiency; the MSA aims to address both by consolidating search results from multiple engines into a single interface. This can significantly reduce the time and effort required to gather relevant information, allowing researchers to focus on analysis and synthesis. You can explore the project and contribute here: zumatt/msa I welcome contributions from the wider research community – whether it be suggestions for additional search engines, identification of bugs, or other improvements. Collaborative development will ensure that MSA continues to evolve and meet the evolving needs of academic researchers.

A Note on My Research Context

From February 2025, I’ll be undertaking my PhD at the Universitat de Vic – Universitat Central de Catalunya (UVic-UCC), within the Elisava Research group and Scuola universitaria professionale della Svizzera italiana (SUPSI). The development of this tool represents an initial step in a year-long research endeavour.

How to cite this page:

Subet, Matteo (2025). Ledger: Multi Search Aggregator. Retrieved on 18 December 2025 from zumat.ch/ledger/multi-search-aggregator.html