The development of domain-specific knowledge graphs has the potential to revolutionize the way social progress is achieved. By providing reliable and actionable data insights, these graphs can help inform the decisions of nonprofits, foundations, government agencies, social entrepreneurs, impact investors, academic institutions, and the general public. This is exemplified by the Social-Impact Funding Knowledge Graph highlighted in this research paper, which has already produced promising results when validated by subject matter experts.
The same methodology used to construct the Social-Impact Funding Knowledge Graph can be applied to other domains, creating more comprehensive knowledge graphs. This paper outlines the challenges of this process, as well as potential solutions and lessons learned.
The potential of domain-specific knowledge graphs to revolutionize social progress is clear. By providing reliable and actionable data insights, these graphs can help inform the decisions of those working to create social impact. This could lead to more efficient and effective use of resources and, ultimately, greater social progress.
AI has the potential to play a major role in this process, and the development of domain-specific knowledge graphs could be a major step forward in leveraging AI for social progress.
Research Paper abstract
Web and mobile technologies enable ubiquitous access to information. Yet, it is getting harder, even for subject matter experts, to quickly identify quality, trustworthy, and reliable content available online through search engines powered by advanced knowledge graphs. This paper explores the practical applications of Domain Specific Knowledge Graphs that allow for the extraction of information from trusted published and unpublished sources, to map the extracted information to an ontology defined in collaboration with sector experts, and to enable the public to go from single queries into ongoing conversations meeting their knowledge needs reliably. We focused on Social-Impact Funding, an area of need for over one million nonprofit organizations, foundations, government entities, social entrepreneurs, impact investors, and academic institutions in the US.
Download the full paper for free by clicking here, thanks to the authors: Ying Li (AI4SP.org Scientific Advisor), Vitalii Zakhozhyi, Daniel Zhu, and Luis J. Salazar (AI4SP.org Founder)