HegemonicBackdrops_LP

In 2008, Chris Anderson, then editor of Wired magazine, suggested that the rise of “big data” marks an “end of theory” where numbers can speak for themselves. Social analysts on big data (such as danah boyd and Kate Crawford) have suggested that such claims propagate a “mythology of objectivity.”
 * “Trust in Numbers” (Porter)**

A dominant theme running through open data movement discourse suggests that with more open data comes more government and commercial transparency – that it’s possible to trace in/action when data is made publically available. While there’s no doubt that some people are doing super cool things with this data, This tends to obscure that publically available data is curated and that even when data is made available, it often requires special technical skill to manipulate.
 * Openness = Transparency**

Since the WWW took off, its decentralization (that there is no central registry for hyperlinks) was seen as one of the key design considerations leading to its success/growth. The Semantic Web adopts a similar philosophy, suggesting that the capacity to link data in a grassroots fashion will scale into a World Wide Web of data (that is notably much smarter than the Web today).
 * Decentralization = Potential for Scalability**

David Golumbia, commenting on the culture of computation that undergirds computer scientists’ love for object-oriented programming, suggests that there is an underlying assumption, in such thinking, that the world can divided into discrete objects and organized hierarchically. This type of thinking is present in Semantic Web engineering, but in a slightly different way – with the focus on the significance of relationships between objects rather than data points themselves as objects.
 * “Computationalist Order” (Golumbia)**

"rationalistic tradition" "world according to logic"
 * Ways of writing about AI**