The latest discipline to benefit from big data analysis is the emerging field of digital humanities. Digital humanities bring artificial intelligence (AI) and text analytics to traditional arts and humanities scholarship. An interesting article in The Irish Times revealed how AI and text analytics approaches were applied to humanities to probe texts running to thousands of pages.
Thousands of data repositories available on the web provide access to millions of datasets. Similarly, local and national governments around the world are also publishing their data. To enable scientists and journalists access this data, Google has launched the Dataset Search. According to Natasha Noy, research scientist at Google AI, this product would help anyone to find the data required for their work or to simply satisfy their intellectual curiosity.
What users expect from search has evolved. In fact, you can demarcate the evolution as B. G. and A. G.—before Google and after Google. Before Google, users were happy with the results that had a semblance of relevance. After its advent, users expect “psychic search” even from enterprise search engines. Psychic search is a type of search that, like Google, just seems to know the intended meaning of a query. According to Miles Kehoe, founder of New Idea Engineering, Google and other public web search and ecommerce sites have evolved along with the changing user expectations. He adds that they have morphed from "web search sites" into “machine-learning matching systems".
Taxonomies and the businesses they serve are constantly evolving and flourishing alongside each other. Similarly, users along with the processes they work with and the content they create and consume are ever evolving. Therefore, it is important to keep the entire vocabulary in mind when adding new terms or making changes to the existing terms. Only then can it be ensured that the taxonomy grows holistically. According to Jenni Doughty, a taxonomist at Enterprise Knowledge, this is a challenging task.
Today, when scientists attempt to conduct a systematic literature review, the number of papers on a topic overwhelms them. However, there is a bevy of new AI-based search tools offering targeted navigation of the knowledge landscape. In fact, developers are looking to leverage these tools to automate how hypotheses are generated and validated, writes Andy Extance, freelance science journalist for Nature —an international journal of science.