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Constructing Data

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As a model of knowledge, datasets not only represent information for the purposes of study.  They also embody a range of ideas and practices related to the broader politics of representation, inclusion, and access. Therefore, as Trevor Owens of the Library of Congress explains, constructing a dataset requires careful "choices about what and how to collect and how to encode the information" [1]. 

Collecting

Roopika Risam (on reproducing colonial knowledge and also on archive that contextualize colonial knowledge- think of Vanishing Race)
Participatory and Community Based archive- example Lesbian Herstory Archives pg 140 Intersectional Feminism
Posner radical new digital humanities (shifts focus from mainstream to marginalized but also develops ways of representing people's lives in data "as they have been experienced, not as they have been captured and advanced by businesses and governments".

Collection Activity

Encoding

For digital collections, item information is frequently encoded in relational databases.  A relational database is a structured set of data that contains a series of formally described tables from which data can be queried or organized in different ways. This structure enhances searching, browsing, and exhibition functions by enabling users to access items and reassemble collections based on tabular information.
To create a collection with these functions, you can either build a relational database or use a content management system (CMS) that functions as a relational database [2]. 

Either way, before getting started you will want to develop a metadata schema for your collection. Metadata, or data about data, "provides a means of indexing, accessing, preserving, and discovering digital resources" [3]. While metadata can serve different functions related to these tasks, in this workshop we will be primarily concerned with its descriptive function [4]. Specifically, you will learn to encode individual items with descriptive metadata and develop a schema to ensure that all of the items in your collection are described consistently to facilitate human and computational analysis.

To create your metadata schema, it is generally advisable to build upon established ontologies and/or controlled vocabularies. Not only will this help you structure your data, but, ultimately, it will allow you to integrate your collection into Linked Data initiatives. For the purposes of this workshop, we will build our schemas on Dublin Core (DC), which is one of the most popular ontologies for describing digital resources. Dublin Core consists of fifteen elemental terms (in italics below) and a series of qualified terms that extend or refine the fifteen elements. 
Before moving to the next activity, where you will build a metadata schema based on Dublin Core terms, it is worth drawing attention to some alternatives and ontological critiques. While Dublin Core is explicit in its cross-disciplinary aim to transcend the " boundaries of information silos on the Web and within intranets," you may have a collection that calls for a more specialized ontology, such as the VRA Core for visual culture, the PBCore for audiovisual content, and the IPTC for media resources [5].  Alternatively, you might have a collection that pushes you to reject established ontologies altogether. For example, as Michelle Schwartz and Constance Crompton write about Lesbian and Gay Liberation in Canada (an interactive digital resource for the study of lesbian, gay, bisexual, and transgender history in Canada from 1964 to 1981):  "rather than flattening data into binaries to fit existing data models and international standards, we strive to represent uncertainty, historical contingency, conflict, variation, instability, and multidimensionality. The stakes are high: in an age where we recognize the right to be forgotten, we must also weight the danger... of hiding our history" [6]. Accordingly, the objective of the next activity is to practice using metadata to structure a collection, not to convince you that all collections should be encoded with Dublin Core.

Metadata Schema Activity

In this activity you will develop a metadata schema for your collection based on Dublin Core. Your schema should include your selected DC terms with collection-specific directions and examples for each term (along the lines of the example below).  
To complete this activity, consult the Dublin Core Elements and Qualifiers manuals; note that each term is optional and can be repeated; and keep in mind that you can link DC terms, like "subject" or "coverage," to controlled vocabularies, such as those developed by the Library of Congress and Getty Institute. 
 

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  1. Data for Humanists Andrea Davis

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