Data management in Systems biology II - Outlook towards the semantic web

TL;DR

The paper discusses how ontologies and semantic web standards can enhance data management in systems biology, addressing current challenges and exploring future AI-driven data search and mining for true knowledge systems.

Contribution

It provides an overview of ontology use in data enrichment, identifies challenges in achieving a semantic web, and offers outlooks on AI and agents for advanced data management.

Findings

Ontologies improve data semantic enrichment.

Current challenges hinder the realization of a true semantic web.

AI and agents are promising for future data search and mining.

Abstract

The benefit of using ontologies, defined by the respective data standards, is shown. It is presented how ontologies can be used for the semantic enrichment of data and how this can contribute to the vision of the semantic web to become true. The problems existing today on the way to a true semantic web are pinpointed, different semantic web standards, tools and development frameworks are overlooked and an outlook towards artificial intelligence and agents for searching and mining the data in the semantic web are given, paving the way from data management to information and in the end true knowledge management systems.