|
課程名稱 |
研究資料基礎架構
Research Data Infrastructure |
|
開課學期 |
107-2 |
|
授課對象 |
文學院 圖書資訊學研究所 |
|
授課教師 |
鄭 瑋 |
|
課號 |
LIS5089 |
|
課程識別碼 |
126 U1520 |
|
班次 |
|
|
學分 |
3.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
星期四6,7,8(13:20~16:20) |
|
上課地點 |
圖資編目室 |
|
備註 |
碩士班與博士班學生均可選修。
限碩士班以上 或 限博士班
總人數上限：20人 |
|
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1072LIS5089 |
|
課程簡介影片 |
|
|
核心能力關聯 |
核心能力與課程規劃關聯圖 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
According to Research Data Alliance (RDA), research data infrastructure (RDI) means resources, technologies, workforce, and services that can effectively and efficiently support research data activities in all disciplines. With the emergence of open science, there are some RDI sub-domains such as data storage, metadata standards, data curation, data sharing, have become notable research topics in LIS and IS communities.
This course aims to help graduate students take a deep dive into state-of-the-art topics on research data and its infrastructure. The course consists of four broad modules: e-Research (cyber-infrastructure), the life cycle of research data production (create, process, cleansing, analysis, store and archives), research data management, giving access to research data.
|
|
課程目標 |
At the conclusion of this class, the students will be able to
- Articulate concepts in a research data lifecycle, including data production, processing, archives, and giving access to others.
- Describe research data infrastructure challenges and opportunities in digital repositories and academic libraries
- Understand data curation profiling tools and relative assessments for scholars’ needs.
- Articulate the concept of open science by further describing data availability, data transparency, and citizen engagement.
|
|
課程要求 |
|
|
預期每週課後學習時數 |
|
|
Office Hours |
|
|
指定閱讀 |
see syllabus |
|
參考書目 |
There is no required textbook for this course. Instead, there are about 3-6
materials each week, which may include books, academic articles, or technical
reports. For the full version of reference, please refer to attached reference
for each week. |
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
Term project- emerging RDI issues |
50% |
including literature maps, annotated bibliography, presentation, and write-ups |
2. |
Class discussion facilitation |
20% |
leading a reading discussion session with presentation or guides |
3. |
Overall Participation |
35% |
including weekly discussions, research notes and hand-on practices and essays |
|
|
週次 |
日期 |
單元主題 |
|
第1週 |
|
Intro; course overview |
|
第2週 |
|
Infrastructure; Cyber-infrastructure; Data lifecycle |
|
第3週 |
|
Class activities: Data production (collecting, cleansing, processing, analyzing) and research process |
|
第4週 |
|
Data storage & preservation, repositories and archives; OAIS |
|
第5週 |
|
no class- iConference |
|
第6週 |
|
no class- Spring break |
|
第7週 |
|
Research data management (RDM): context, policies and impacts; Research Data Services (RDS) |
|
第8週 |
|
Data curation and curation profiling tools |
|
第9週 |
|
Data standards and metadata |
|
第10週 |
|
Data and scholarly communication: data publication; data citation |
|
第11週 |
|
Immersive Session: Interview “data” with faculty researcher (CSIE) |
|
第12週 |
|
Midterm checkpoint presentation |
|
第13週 |
|
Open science topics-I: Data availability (data sharing & reuse) and accessibility |
|
第14週 |
|
Open science topics-II: Data quality; transparency & reproducibility |
|
第15週 |
|
Open science topics-III: Citizen science and public libraries |
|
第16週 |
|
Student presentation- Emerging RDI issues |
|
第17週 |
|
Student presentation- Emerging RDI issues |
|