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开源软件名称:visualizedata/data-structures开源软件地址:https://github.com/visualizedata/data-structures开源编程语言:JavaScript 48.9%开源软件介绍:Parsons School of Design, The New School Data StructuresPGDV 5110 Syllabus, Fall 2021Wednesdays, 12:10pm - 2:50pm Faculty: Aaron Hill | Office Hours: Fridays 3:00pm - 4:00pm: no appointment needed; contact info and Zoom info in Canvas Teaching Assistant: Jessie Han | Office Hours: Mondays 11:00am - 12:00pm and Thursdays 4:00pm - 5:00pm: no appointment needed; contact info and Zoom info in Canvas I encourage use of the Canvas discussion board for collaboration and work on assignments, including the 10 weekly and 3 final assignments. All questions/issues about the assignments should be posted here, building a shared knowledge base in the process. Questions/issues raised in office hours should also be posed here prior to the office hour meeting and the answer/resolution will be posted by the person who originally posed the question. Course description: Curating raw data presents issues of technology, speed, and efficiency, as well as broader ethical considerations of what it means to represent and make conclusions about groups and individuals from their data. This course covers the database, semi-structured data, and unstructured data. Students will gain familiarity with underlying data structures; techniques and tools, including acquisition, augmentation, and restructuring; data storage and aggregation; access to parallel and distributed computing; high-volume data, disparate sources, and performance; and streaming data, real time, and dynamic queries. Prerequisites: Basic knowledge of JavaScript, HTML/CSS, Linux command line, Git, and GitHub. Course Overview
Course OutlineSeptember 1 (Week 1)Introduction to data structures. Weekly Assignment 1, due Tuesday 9/7 at 6:00pm: Documentation:September 8 (Week 2)The web as a database. "Raw data." Read:
Weekly Assignment 2, due Tuesday 9/14 at 6:00pm: Documentation:September 15 (Week 3)Fundamental data structures. Data augmentation and integration. GitHub for open source collaboration. Read:
Weekly Assignment 3, due Tuesday 9/21 at 6:00pm: Documentation:
September 22 (Week 4)Data models I: SQL database. Read:
Weekly Assignment 4.1, due Tuesday 9/28 at 6:00pm: Documentation:September 29 (Week 5)Data models I: NoSQL database. Read:
Weekly Assignment 5.1, due Tuesday 10/5 at 6:00pm: Final Assignment 1 distributed: Map of AA meetings in Manhattan. Final Assignment 2 distributed: "Process Blog," a source of semi-structured, qualitative data. October 6 (Week 6)The Query. Indexes, joins, query optimization, and data restructuring. The E-R model. Data provision. Read:
Weekly Assignments 4.2 and 5.2, due Tuesday 10/19 at 6:00pm: 5.2: You will create a new managed DynamoDB database, and write code to populate your database with your "Process Blog" data. (2.5 points) October 13 (Week 7)Data cleaning. Logging issues. Data cleaning workshop. Weekly Assignment 6, due Tuesday 10/19 at 6:00pm: Read:
Documentation:October 20 (Week 8)Note: IEEE VIS virtual conference is October 24-29 Sensors. Data gathering and surveillance. Weekly Assignment 7, due Tuesday 11/2 at 6:00pm: Read:
Documentation:October 27 (Week 9)[slides] IoT. Note: IEEE VIS virtual conference is October 24-29 DUE Wednesday 11/4 at 12:00pm: IEEE VIS conference presentation summary Read:
November 3 (Week 10)From database to visual representation. Interface design. Workshop by Jessie Han: How to create filters on the front end. Weekly Assignment 8, due Tuesday 11/9 at 6:00pm: Final Assignment 3 distributed: Surveilling your life. Debate: SQL vs. NoSQL 1/2 | 3/4] Read:
November 10 (Week 11)Serverless computing. Workshop by Jessie Han: Use python + flask to host a website. Weekly Assignment 9, due Tuesday 11/16 at 6:00pm: Read:Documentation:November 17 (Week 12)Discussion: Reliability. Lab. Coding demo: making a map in mapbox Weekly Assignment 10, due Tuesday 11/30 at 6:00pm: Read:
Groups for Reliability, Scalability, and Maintainability Discussions:
November 24: No class, Thanksgiving holidayDecember 1 (Week 13)Discussion: Scalability. When do you need a database(s)? When do you not? Lab. Read:
December 8 (Week 14)Discussion: Maintainability. Lab. Read:
Final Assignments 1, 2, and 3 due Tuesday 12/14 at 6:00pm: December 15 (Week 15)In the final class meeting, you will present your work in groups, by theme. Group and theme assignments:
Terminating and cleaning up your AWS resources and credentials. [checklist] Learning OutcomesBy the successful completion of this course, students will be able to demonstrate:
Final Grade Calculation
Weekly assignments are worth 5 points each, unless otherwise indicated. They are due 6:00pm the Tuesday after they are assigned, unless otherwise indicated. The quality of your documentation is a part of the grade for every assignment, including all the weekly and final assignments. All documentation must be kept in your (well organized!) Late assignments:If an assignment is less than 48 hours late, the maximum possible grade is 75%. Required Reading"Raw Data" Is an Oxymoron, Lisa Gitelman, 2013. This book is available electronically through course reserves. Recommended/Optional ReadingDatabase Aesthetics : Art in the Age of Information Overflow, Victoria Vesna. This book is available electronically through course reserves. Office Hours (Zoom; no appointment needed)Fridays, 3:00pm - 4:00pm Materials and SuppliesIn this course we will rely exclusively on open source software and we will work with the software by writing code: JavaScript, SQL, and some basic Linux. We will also rely on cloud-based services to provide infrastructure, platforms, and computational power:
Required:
ResourcesThe university provides many resources to help students achieve academic and artistic excellence. These resources include:
In keeping with the university's policy of providing equal access for students with disabilities, any student with a disability who needs academic accommodations must contact SDS. There are several ways for students to contact the office: via email at [email protected], through the Starfish service catalog, or by calling the office at 212.229.5626. A self-ID form can also be completed on the SDS webpage at www.newschool.edu/student-disability-services. Once you contact the office, SDS staff will arrange an intake appointment to discuss your concerns and, if appropriate, provide you with accommodation notices to give to me. Please note that faculty will not work unilaterally with students to provide accommodations. If you inform me of a disability but do not provide any official notification, I must refer you to SDS. Making CenterThe Making Center is a constellation of shops, labs, and open workspaces that are situated across the New School to help students express their ideas in a variety of materials and methods. We have resources to help support woodworking, metalworking, ceramics and pottery work, photography and film, textiles, printmaking, 3D printing, manual and CNC machining, and more. A staff of technicians and student workers provide expertise and maintain the different shops and labs. Safety is a primary concern, so each area has policies for access, training, and etiquette with which students and faculty should be familiar. Many areas require specific orientations or trainings before access is granted. Grading StandardsA Work of exceptional quality Grades of D are not used in graduate level courses. Grade of W: Unofficial Withdrawal (Grade of Z): Grades of Incomplete:
College, School, Program and Class Policies:A comprehensive overview of policy may be found under Policies: A to Z. Students are also encouraged to consult the Academic Catalog for Parsons. CanvasUse of Canvas may be an important resource for this class. Students should check it for announcements before coming to class each week. Electronic DevicesThe use of electronic devices (phones, tablets, laptops, cameras, etc.) is permitted when the device is being used in relation to the course's work. All other uses are prohibited in the classroom and devices should be turned off before class starts. ResponsibilityStudents are responsible for all assignments, even if they are absent. Late assignments, failure to complete the assignments for class discussion and/or critique, and lack of preparedness for in-class discussions, presentations and/or critiques will jeopardize your successful completion of this course. Active Participation and AttendanceClass participation is an essential part of class and includes: keeping up with reading, assignments, projects, contributing meaningfully to class discussions, active participation in group work, and coming to class regularly and on time. Parsons' attendance guidelines were developed to encourage students’ success in all aspects of their academic programs. Full participation is essential to the successful completion of coursework and enhances the quality of the educational experience for all, particularly in courses where group work is integral; thus, Parsons promotes high levels of attendance. Students are expected to attend classes regularly and promptly and in compliance with the standards stated in this course syllabus. While attendance is just one aspect of active participation, absence from a significant portion of class time may prevent the successful attainment of course objectives. A significant portion of class time is generally defined as the equivalent of three weeks, or 20%, of class time. Lateness or early departure from class may be recorded as one full absence. Students may be asked to withdraw from a course if habitual absenteeism or tardiness has a negative impact on the class environment. I will assess each student’s performance against all of the assessment criteria in determining your final grade. |
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