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課程名稱 |
研究資料基礎架構
Research Data Infrastructure |
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開課學期 |
108-2 |
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授課對象 |
文學院 圖書資訊學研究所 |
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授課教師 |
鄭 瑋 |
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課號 |
LIS5089 |
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課程識別碼 |
126 U1520 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期三6,7,8(13:20~16:20) |
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上課地點 |
圖資編目室 |
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備註 |
總人數上限：18人 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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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. |
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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. |
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課程要求 |
待補 |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
待補 |
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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. |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第1週 |
2/19 |
Intro; course overview |
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第2週 |
2/26 |
Infrastructure; cyber-infrastructure; data lifecycle |
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第3週 |
3/04 |
Class activities: Research process and data production (collecting, cleansing, processing, analyzing) |
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第4週 |
3/11 |
Data storage & preservation, OAIS for data preservation |
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第5週 |
3/18 |
Research data management (RDM): context, policies and impacts; Research support (RS): research data services (RDS) in libraries |
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第6週 |
3/25 |
No class meeting |
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第7週 |
4/01 |
No class meeting |
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第8週 |
4/08 |
Data curation and curation profiling tools |
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第9週 |
4/15 |
Data standards and metadata; data publication & data citation; journal regulations |
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第10週 |
4/22 |
Immersive Session: Interview “data” with research faculty |
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第11週 |
4/29 |
Immersive Session: Interview “data” with research faculty |
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第12週 |
5/06 |
Open science topics-I: Data transparency & reproducibility; data quality |
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第13週 |
5/13 |
Open science topics-II: Data availability (data sharing) and accessibility (reuse) |
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第14週 |
5/20 |
Open science topics-III: Open data- privacy & ethics; Citizen science and public libraries |
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第15週 |
5/27 |
RDI workshop I- Emerging RDI issues |
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第16週 |
6/03 |
RDI workshop II- Emerging RDI issues |
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第17週 |
6/10 |
Debriefing (TBA) |
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