This is a full length monograph aimed at helping libraries, archives, and museums navigate copyright law involving digitization. In the course of the book, though, the authors helpfully unpack many areas of copyright law including Section 108 of the Copyright Act, Fair Use, Licensing, and Risk Management. It is a great primer on copyright law and includes many helpful key points, flowcharts and timelines.

Overview: This survey instrument is designed to understand how creators use (or decide not to use) Creative Commons licenses. The target survey participants are people who create materials for documentation, maintenance, instruction, learning, and/or revitalization of Indigenous, minority, endangered, and/or low-resourced languages. Part 1 of this survey is designed to learn about the digital creation formats and sharing practices in this specific community of practice. Parts 2 through 4 of this survey contain general questions intended to elicit information about research participants’ knowledge and awareness of Creative Commons (CC) licenses; understanding of how to apply CC licenses to their digital creations; interest in and experience with applying CC licenses to their digital creations; motivations for and barriers to applying CC licenses to their digital creations; and understanding of how to adapt or reuse digital creations licensed with CC licenses.

This survey can be easily adapted for use in other communities of practice by editing some of the questions and multiple-choice responses.

If you wish to read this survey and background information about it, please start with the file ReadMe-CCLuseSurvey.pdf.

The file Creative_Commons_License_Use_Survey.qsf is a Qualtrics Survey File that can be used to recreate this survey in your own instance of the Qualtrics software.

The file Creative_Commons_License_Use_Survey.pdf is a PDF of the survey. This version includes Creative Commons graphics that are used in the survey questions. The file ReadMe-CCLuseSurvey.pdf does not include the graphics.

A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.

This course focuses on cyberspace and its implications for private and public, sub-national, national, and international actors and entities.

The MIT Libraries Data Management Group hosts a set of workshops during IAP and throughout the year to assist MIT faculty and researchers with data set control, maintenance, and sharing. This resource contains a selection of presentations from those workshops. Topics include an introduction to data management, details on data sharing and storage, data management using the DMPTool, file organization, version control, and an overview of the open data requirements of various funding sources.

Introduces students to a class of methods known as data mining that assists managers in recognizing patterns and making intelligent use of massive amounts of electronic data collected via the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Topics covered: subset selection in regression, collaborative filtering, tree-structured classification and regression, cluster analysis, and neural network methods. Examples of successful applications in areas such as credit ratings, fraud detection, database marketing, customer relationship management, and investments and logistics are covered. Hands-on experimentation with data-mining software is used. Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. We will survey applications and provide an opportunity for hands-on experimentation with algorithms for data mining using easy-to- use software and cases.

This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.

The book offers a blend of theory and practice in guiding readers to apply design thinking principles to solving some of our world’s biggest problems. At the same time, readers are encouraged to become aware of new and emerging technologies that make prototyping and applying solutions a reality.

Le but de ce manuel est de vous donner les connaissances de base nécessaires pour commencer à rechercher des informations en utilisant le catalogue et les bases de données de la bibliothèque de l’Université d’Alberta. Le manuel contient des instructions étape par étape, des vidéos et des exemples en sciences humaines et sociales. Pour atteindre les objectifs prévus, il vous faudra passer au moins une heure et demie à lire les instructions du didacticiel, répondre aux questions des exercices et revoir les exemples chaque fois que cela sera nécessaire.

Differentiating open access and open educational resource can be a challenge in some contexts. Excellent resources such as "How Open Is It?: A Guide for Evaluating the Openness of Journals" (CC BY) https://sparcopen.org/our-work/howopenisit created by SPARC, PLOS, and OASPA greatly aid us in understanding the relative openness of journals. However, visual resources to conceptually differentiate open educational resources (OER) from resources disseminated using an open access approach do not currently exist. Until now.

This one page introductory guide differentiates OER and OA materials on the basis of purpose (teaching vs. research), method of access (analog and digital), and in terms of the relative freedoms offered by different levels of Creative Commons licenses, the most common open license. Many other open licenses, including open software licenses also exist.

An instructional text that seeks to untangle the social complexities and ethical dilemmas of online data and information. DIGITAL CITIZENSHIP will educate readers on the economics of the Internet and the means by which political bad actors exploit its platforms to pervert the public discourse.

Hello and welcome to the Digital Citizenship Toolkit. Have you ever wondered if your phone is listening to you? Do you ever look to the Internet for the answer to a question, and hours later, find that you are more confused than before? Have you argued with a friend or relative about a meme? Have you been tempted to share your own thoughts and feelings online, but resisted for fear of trolls? This book delves into these issues and more.

A modules-based approach to learning research skills that emphasizes the reflective nature of information discovery, the contextual basis for evaluating that information, and a recognition that information has value.

The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.

This resource is used to provide library instruction for introductory undergraduate composition courses.

This resource is used for library instruction in undergraduate second semester composition courses

The onset of new, more accessible, artificial intelligence (AI) technologies marks a significant turning point for libraries, ushering in a period rich with both unparalleled opportunities and complex challenges. In this era of swift technological transformation, libraries stand at a critical intersection. To effectively chart this transition, two quick polls were conducted among members of the Association of Research Libraries (ARL).

The first poll, which ran in April 2023, provided an initial snapshot of the AI landscape in libraries. The second poll, carried out in December 2023, continued this inquiry, offering a comparative perspective on the evolving dynamics of AI use and possibilities in library services. This study analyzes and juxtaposes the outcomes of these two surveys to better understand how library leaders are managing the complexities of integrating AI into their operations and services. It specifically seeks to capture changing perspectives on the potential impact of AI, assess the extent of AI exploration and implementation within libraries, and identify AI applications relevant to the current library environment.

The insights derived from this comparative analysis shed light on the role of libraries in an increasingly AI-driven era, providing strategic directions and highlighting practices in research libraries.

This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.

Topics covered include:

Clinical Financial Records
Evidence-Based Medicine
e-Prescribing
Patient Bedside Systems
Telemedicine
Health Information Networks
Cryptography
Accreditation
HIPAA Privacy and Security

This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

This course is a collaborative offering of Sana, Partners in Health, and the Institute for Healthcare Improvement (IHI). The goal of this course is the development of innovations in information systems for developing countries that will (1) translate into improvement in health outcomes, (2) strengthen the existing organizational infrastructure, and (3) create a collaborative ecosystem to maximize the value of these innovations. The course will be taught by guest speakers who are internationally recognized experts in the field and who, with their operational experiences, will outline the challenges they faced and detail how these were addressed.This OCW site combines resources from the initial Spring 2011 offering of the course (numbered HST.184) and the Spring 2012 offering (numbered HST.S14).