CoreCategories_LP

(and Chapter summaries)
 * Section 1: Structure **

In this section, I will recount the history of the Web, describing how, from the outset, the Web’s success was attributed to the lightness of its structure and its capacity to tolerate error. [stories that informants tell about the success of the WWW]
 * What kind of information infrastructure is the Web? **

This section will consider how database structures have transformed since the early 1970s, reflecting changing information commitments. I will discuss what sorts of information configuration and knowledge representation each of these structures affords.
 * From relational database to object-oriented database to Semantic Web (graph database) **

In this section, I will consider the types of governance structures that enable environmental justice communities to go undocumented. I will draw on STS literature on organized ignorance and the way that expert systems can produce it.
 * Case material: Structural environmental injustices **


 * Section 2: Semiotics **

In this section, I will recount the history of the neat/scruffy distinction in AI. I will articulate how each of these communities brings to their work different understandings of how meaning functions (as something internally consistent or as something emergent).
 * Neats vs. the scruffies **

In this section, I will hone in specifically on my analysis of the data formats that enable the Semantic Web – the syntax for the Semantic Web. Specifically, I will discuss XML and RDF, and how and why Semantic Web practitioners see //linking// data in subject-predicate-object form as a better structure for representing the world’s information.
 * Syntax: The structure of Linked data formats **

In this section, I will hone in specifically on my analysis of standard Web vocabularies such as Schema.org and standard Web ontologies such as the Web Ontology Language (OWL). I will consider how they shape the way data can be classified and organized. I will also discuss how researchers that have been involved in the design of the Semantic Web understand the significance of giving data meaning or “semantics.”
 * Semantics: Vocabularies and ontologies (including OWL) **

In this section, I will draw on case material to describe how the Semantic Web’s data formats, vocabularies and ontologies shape how meaning can be made for environmental justice communities.
 * Case material: Semiotic environmental injustices **


 * Section 3: Limits **

Today, neats are increasingly becoming open to systems characterized by greater flexibility. In this section, I will discuss the how the limits of infrastructure, the limits of language, and the limits of interdisciplinarity are pushing AI researchers and information infrastructure developers to new limits. I will articulate the double binds of information infrastructure and how information practitioners work against these binds. I will draw out an ethnographic argument about how Semantic Web practitioners approach the limits of infrastructure and knowledge representation.

In this section, I will draw on my case material to describe the limits of representing environmental justice communities. I will recount the data factors that make it difficult to bring such communities to the fore and also describe how the binds of information infrastructure make comprehensive representation impossible.
 * Case material: The limits of EJ representation **


 * Section 4: Justice **

In this section, I will discuss the concept of devious design and how it can be leveraged to work against the limits of knowledge representation structured by information infrastructures.
 * Devious/tricky design **

Acknowledging that no amount of representing can ever fully the capture the Other, in this section, I will consider what fairness in environmental justice representation might look like and the information infrastructure that can best approach that goal.
 * Case material: Information infrastructural justice **