Updated: Concept Map on Data, Power, & Silence

Lancez-Vous. C'est gratuit
ou s'inscrire avec votre adresse e-mail
Updated: Concept Map on Data, Power, & Silence par Mind Map: Updated: Concept Map on Data, Power, & Silence

1. Power: influence, authority, and control over the telling of history

1.1. Power is a integral component of narratives and silence

1.1.1. Power includes the ability to exclude/censure information

1.1.2. Narratives are constructed through the power an authority has over data and its presentation

1.2. Selection of sources/framing of questions/intepretation of evidence

1.2.1. Ties back to narrative as construction of history is influenced about how the data is presented/interpreted

1.3. Power dynamics in institutions/systems/society

1.3.1. For example, Kings can decide how a story of his kingdom is told and can censure what he does not like

1.3.1.1. Is this account a true account of history?

1.3.2. Institutions such as universities, libraries, museums, and government agencies exert power in determining funding priorities, research agendas, and access to resources

1.4. metadata

1.4.1. power affects the use of this data type

1.5. "Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic" (D'Ignazio and Klein 2020).

1.5.1. The power that data science holds and Data feminism goes for the throat in its opening

1.5.2. this quote (and article) give a good understanding of intersectionality

1.6. data visualization

1.6.1. Those who control the visualization have the power to shape the narrative.

1.6.2. Visualizations can be manipulated to emphasize certain points or perspectives, potentially leading to biased interpretations

1.7. Geospatial Visualization

1.7.1. Maps can be manipulated to emphasize certain areas or de-emphasize others, potentially leading to biased interpretations

1.8. Statistical Analysis

1.8.1. Those who conduct and interpret statistical analyses hold significant power in shaping the narrative

1.9. Network Analysis

1.9.1. can reveal power dynamics and key influencers

1.9.1.1. structure of network and distribution of power

1.10. Text Analysis

1.10.1. deciding which texts to include and which aspects to emphasize

2. Silence: the ommission or absence of data from historical accounts

2.1. Trouillot points out that narratives silence voices, events, and perspectives

2.1.1. exclusion of data

2.1.2. margnilization of data

2.2. data visualization

2.2.1. Visualizations can also contribute to "silence" by omitting certain data points or perspectives

2.2.1.1. intentionally or unintentionally and can lead to incomplete or skewed narratives

2.3. Gaps in historical data

2.3.1. Is data really missing or was it intentionall left out?

2.3.1.1. Narrative uses silence to construct its perspective

2.4. Significance of events depends on narrative

2.4.1. Western civilization is a great example of silence

2.4.1.1. The dominant perspective of many modern historical accounts is seen through a western lens

2.5. How can we be sure history is complete?

2.5.1. What's missing?

2.6. Geospatial Visualization

2.6.1. omitting certain data points or regions

2.6.1.1. marginalized communities, may be underrepresented or misrepresented in maps

2.6.1.2. "Hawk Cuzco" example of having to portray their map in a eurocentric style

2.7. Statistical Analysis

2.7.1. variables or dimensions of the data might be overlooked or ignored

2.8. Network Analysis

2.8.1. exclusion or ommision of data will marginalize relationships between entities

2.9. Text Analysis

2.9.1. excluding certain texts, voices, or perspectives

2.9.2. Analyzing what is missing from the text data can reveal silences and gaps

3. Narrative: structured and intepretive accounts of historical, cultural, social events

3.1. Idea of Victor writiting history

3.1.1. Uses data to construct a narrative that fits their perspective

3.2. Historical accounts are not objective but are influenced by the intepretation of who is writing it (generalizing the idea of a victor writing history

3.2.1. The way Data is intepreted affects the judgement and context that the data is intepreted

3.2.1.1. the meaning and significance of events can change depending on the biases

3.3. Trouillot emphasizes the power that narrative has in contructing historical data

3.3.1. Opens idea of trying to find the other side of history to counter any possible biases

3.4. How can we be sure that history is being told as objectively as possible?

3.4.1. Important to keep in mind biases to look at history through different perspectives

3.5. In "Maps are Territories", "Hawk Puma" who centered his map with the Inca capital Cuzco and oriented north, east, west, and south differently than a traditional map (Turnbull, 2008)

3.5.1. A great example of narrative is the creation of maps

3.5.1.1. who decides the general structure of maps

3.5.1.1.1. orientation

3.5.1.1.2. size/shape

3.5.1.1.3. color

3.5.1.2. Also connects to power, as those in control tell the story

3.6. data visualization

3.6.1. Charts and graphs can provide context to data, helping to illustrate not just the "what" but the "why" and "how"

3.6.2. engaging visuals can make story more memorable

3.7. Geospatial Visualization

3.7.1. bring historical and cultural narratives to life by showing how events and phenomena are distributed across space and time

3.8. Statisical Analysis

3.8.1. empirical foundation for narratives, allowing for data-driven storytelling

3.8.1.1. libraries and the contents of their books as well as who wrote the book creates a foundation for a story

3.9. Network Analysis

3.9.1. tell compelling stories by illustrating how entities are interconnected

3.9.2. track changes over time

3.9.2.1. enhance storytelling

3.10. Text Analysis

3.10.1. supports narrative construction by identifying themes and patterns

4. Data: quantifiable and qualitive

4.1. numbers/pictures/objects used in conjunction with time

4.1.1. historians will visualize data over time to build an understanding of it

4.2. Data Visualization

4.2.1. Charts/Grahs

4.2.2. "a map is a kind of visualization that uses levels of abstraction, scale, coordinate systems, perspective, symbology, and other forms of representation to convey a set of relations" (Presner & Shepard, 2016)

4.2.2.1. ultimately data wants to be visualized

4.2.2.1.1. acessibility

4.2.2.1.2. faster interpretation

4.2.2.1.3. easier to see patterns/trends

4.3. metadata

4.4. Geospatial visualization

4.4.1. Mapping data geographically can reveal patterns and relationships that are not immediately obvious in non-spatial formats

4.5. Network Analysis

4.5.1. analysis of social networks, communication patterns, and interconnections among entities

4.6. Text Analysis

4.6.1. converts unstructured textual data into structured information that can be quantified and analyzed

4.7. datasets can/will tell a story and it depends on the narrator how that story unfolds

4.7.1. Data should be accessible to anyone that wants to analyze and intepret it themselves.

4.7.1.1. organized

4.7.1.2. Statistical Analysis

4.7.1.3. easy to read

4.7.1.4. easy to use

4.8. Accuracy of Data depends on the consistency and reliability of it

4.8.1. Consistency and reliability are built through patterns and repetition

5. Intersectionality: framework for understanding how various aspects of a person's social and political identities (gender, race, class, sexuality) combine to create unique modes of discrimination and privilege.

5.1. narrative plays a role in how social/political identities are viewed

5.2. Missing female inclusion and voice

5.3. Data is a component in the shaping of identities

5.4. DH Project: Growth of female authors in the 1960s

5.4.1. Use of female protagonists in noevel

5.4.1.1. Actions that helped negate the silence of women's voices in the 1900s

5.5. data feminism

5.5.1. "Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed" (D'Ignazio and Klein 2020)