TIB AIssistant: a Platform for AI-Supported Research Across Research Life Cycles

TL;DR

The paper introduces TIB AIssistant, a comprehensive platform that leverages AI and LLMs to support researchers throughout all stages of the research process, enhancing efficiency, transparency, and reproducibility.

Contribution

It presents a novel, integrated platform with specialized assistants and tools for AI-supported research, including data management and export features for reproducibility.

Findings

Demonstrated AIssistant's functionalities through a research paper draft example

Showcased integration of assistants for different research tasks

Highlighted support for transparency and reproducibility via RO-Crate export

Abstract

The rapidly growing popularity of adopting Artificial Intelligence (AI), and specifically Large Language Models (LLMs), is having a widespread impact throughout society, including the academic domain. AI-supported research has the potential to support researchers with tasks across the entire research life cycle. In this work, we demonstrate the TIB AIssistant, an AI-supported research platform providing support throughout the research life cycle. The AIssistant consists of a collection of assistants, each responsible for a specific research task. In addition, tools are provided to give access to external scholarly services. Generated data is stored in the assets and can be exported as an RO-Crate bundle to provide transparency and enhance reproducibility of the research project. We demonstrate the AIssistant's main functionalities by means of a sequential walk-through of assistants, interacting with each other to generate sections for a draft research paper. In the end, with the AIssistant, we lay the foundation for a larger agenda of providing a community-maintained platform for AI-supported research.