We have outsourced our memory to online search engines, in particular Google, and just search for the ‘fact’ we cannot remember. Even the proprietary name Google, now one of the world’s biggest technology companies,, has transmogrified into a verb: ‘Why don’t you google it?’ Web search engines have become embedded into our daily lives; we view information and knowledge through the lens of a search engine, generating a one-dimensional list-map of the knowledge landscape related to the keyword search query we have served to a ranking algorithm parsing a powerful, but by no means exhaustive, index of information sources. In over 70 per cent of cases,, our process of seeking an information source is satisficed within the first page of results; however, for complex, culturally entangled research questions the most significant sources in the knowledge landscape are rarely near the top of the ranked query results. Not all research resources are accessible through search queries and even knowledge of their existence may not be available to the search engine user.
In many research disciplines where there exist well-known big data datasets which have been collaboratively created or are the output of sensors or other devices, there is little need to use search engines or AI agents for data discovery. However, in disciplines such as the humanities and the social sciences research data may come from disparate sources often held by more than one cultural heritage institution (CHI), accompanied by the kinds of rich contextual flows discussed in Chapter 2.
In this chapter we will discuss the challenges of gaps in the knowledge creation process caused by the process of locating research resources within the human record through search engines and how this is reshaping the response of the traditional keepers of cultural heritage data to the changing ways in which their communities of researchers wish to interact.
|Naam||Bloomsbury Studies in Digital Cultures|