Matching Items (3)
Filtering by
- All Subjects: Databases
- All Subjects: Air--Pollution--Law and legislation--Social aspects--Mexico--Mexico City.
- Genre: Academic theses
- Creators: Duarte, Marisa E.
- Creators: Garcia, Lucero
- Creators: Tyagi, Preetika
- Resource Type: Text
Description
This thesis addresses the problem of online schema updates where the goal is to be able to update relational database schemas without reducing the database system's availability. Unlike some other work in this area, this thesis presents an approach which is completely client-driven and does not require specialized database management systems (DBMS). Also, unlike other client-driven work, this approach provides support for a richer set of schema updates including vertical split (normalization), horizontal split, vertical and horizontal merge (union), difference and intersection. The update process automatically generates a runtime update client from a mapping between the old the new schemas. The solution has been validated by testing it on a relatively small database of around 300,000 records per table and less than 1 Gb, but with limited memory buffer size of 24 Mb. This thesis presents the study of the overhead of the update process as a function of the transaction rates and the batch size used to copy data from the old to the new schema. It shows that the overhead introduced is minimal for medium size applications and that the update can be achieved with no more than one minute of downtime.
ContributorsTyagi, Preetika (Author) / Bazzi, Rida (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Mexico City has an ongoing air pollution issue that negatively affects its citizens and surroundings with current structural disconnections preventing the city from improving its overall air quality. Thematic methodological analysis reveals current obstacles and barriers, as well as variables contributing to this persistent problem. A historical background reveals current programs and policies implemented to improve Mexico’s City air quality. Mexico City’s current systems, infrastructure, and policies are inadequate and ineffective. There is a lack of appropriate regulation on other modes of transportation, and the current government system fails to identify how the class disparity in the city and lack of adequate education are contributing to this ongoing problem. Education and adequate public awareness can potentially aid the fight against air pollution in the Metropolitan City.
ContributorsGarcia, Lucero (Author) / Duarte, Marisa E. (Thesis advisor) / Arzubiaga, Angela (Committee member) / Richter, Jennifer (Committee member) / Arizona State University (Publisher)
Created2018
Description
Software systems can exacerbate and cause contemporary social inequities. As such, scholars and activists have scrutinized sociotechnical systems like those used in facial recognition technology or predictive policing using the frameworks of algorithmic bias and dataset bias. However, these conversations are incomplete without study of data models: the structural, epistemological, and technical frameworks that shape data. In Modeling Power: Data Models and the Production of Social Inequality, I elucidate the connections between relational data modeling techniques and manifestations of systems of power in the United States, specifically white supremacy and cisgender normativity. This project has three distinct parts. First, I historicize early publications by E. F. Codd, Peter Chen, Miles Smith & Diane Smith, and J. R. Abrial to demonstrate that now-taken-for-granted data modeling techniques were products of their social and technical moments and, as such, reinforced dominant systems of power. I further connect database reification techniques to contemporary racial analyses of reification via the work of Cheryl Harris. Second, I reverse engineer Android applications (with Jadx and apktool) to uncover the relational data models within. I analyze DAO annotations, create entity-relationship diagrams, and then examine those resultant models, again linking them back to systems of race and gender power. I craft a method for performing a reverse engineering investigation within a specific sociotechnical context -- a situated analysis of the contextual epistemological frames embedded within relational paradigms. Finally, I develop a relational data model that integrates insights from the project’s reverse and historical engineering phases. In my speculative engineering process, I suggest that the temporality of modern digital computing is incommensurate with the temporality of modern transgender lives. Following this, I speculate and build a trans-inclusive data model that demonstrates uses of reification to actively subvert systems of racialized and gendered power. By promoting aspects of social identity to first-order objects within a data model, I show that additional “intellectual manageability” is possible through reification. Through each part, I argue that contemporary approaches to the social impacts of software systems incomplete without data models. Data models structure algorithmic opportunities. As algorithms continue to reinforce systems of inequality, data models provide opportunities for intervention and subversion.
ContributorsStevens, Nikki Lane (Author) / Wernimont, Jacqueline D (Thesis advisor) / Michael, Katina (Thesis advisor) / Richter, Jennifer (Committee member) / Duarte, Marisa E. (Committee member) / Arizona State University (Publisher)
Created2022