A Brief Introduction to Open Data, Open Source Software and Collective Intelligence for Environmental Data Creators and Users
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Licensing Open Government Data Jyh-An Lee
Hastings Business Law Journal Volume 13 Article 2 Number 2 Winter 2017 Winter 2017 Licensing Open Government Data Jyh-An Lee Follow this and additional works at: https://repository.uchastings.edu/ hastings_business_law_journal Part of the Business Organizations Law Commons Recommended Citation Jyh-An Lee, Licensing Open Government Data, 13 Hastings Bus. L.J. 207 (2017). Available at: https://repository.uchastings.edu/hastings_business_law_journal/vol13/iss2/2 This Article is brought to you for free and open access by the Law Journals at UC Hastings Scholarship Repository. It has been accepted for inclusion in Hastings Business Law Journal by an authorized editor of UC Hastings Scholarship Repository. For more information, please contact [email protected]. 2 - LEE MACROED.DOCX (DO NOT DELETE) 5/5/2017 11:09 AM Licensing Open Government Data Jyh-An Lee* Governments around the world create and collect an enormous amount of data that covers important environmental, educational, geographical, meteorological, scientific, demographic, transport, tourism, health insurance, crime, occupational safety, product safety, and many other types of information.1 This data is generated as part of a government’s daily functions.2 Given government data’s exceptional social and economic value, former U.S. President Barack Obama described it as a “national asset.”3 For various policy reasons, open government data (“OGD”) has become a popular governmental practice and international * Assistant Professor at the Faculty of Law in the Chinese University -
Revolution R Enterprise 6.1 README
Revolution R Enterprise 6.1 README Revolution R Enterprise 6.1 for 32-bit and 64-bit Windows and 64-bit Red Hat Enterprise Linux (RHEL 5.x and RHEL 6.x) features an updated release of the RevoScaleR package that provides fast, scalable data management and data analysis: the same code scales from data frames to local, high-performance .xdf files to data distributed across a Windows HPC Server cluster, Windows HPC Server Azure Burst cluster, or IBM Platform Computing LSF cluster. RevoScaleR also allows distribution of the execution of essentially any R function across cores and nodes, delivering the results back to the user. Installation instructions and instructions for getting started are provided in your confirmation e-mail. What’s New in Revolution R Enterprise 6.1 Big Data Decision Tree Models New RevoScaleR function rxDTree can be used to create decision tree models. It is based on a binning algorithm so that it can scale to huge data. Both classification and regression trees are supported. The model objects returned can be made to inherit from the rpart class of the rpart package, so that plot.rpart, text.rpart, and printcp can be used for subsequent analysis. Prediction for models fitted by rxDTree can be done using rxPredict. See Chapter 10 of the RevoScaleR User’s Guide for examples on how to create decision tree models with rxDTree. Additional information is available in the rxDTree help file, seen by entering ?rxDTree at the R command line. Support for Compression in .xdf Files RevoScaleR’s .xdf files can now be created using zlib compression. -
Digital Rights Management and the Process of Fair Use Timothy K
University of Cincinnati College of Law University of Cincinnati College of Law Scholarship and Publications Faculty Articles and Other Publications Faculty Scholarship 1-1-2006 Digital Rights Management and the Process of Fair Use Timothy K. Armstrong University of Cincinnati College of Law Follow this and additional works at: http://scholarship.law.uc.edu/fac_pubs Part of the Intellectual Property Commons Recommended Citation Armstrong, Timothy K., "Digital Rights Management and the Process of Fair Use" (2006). Faculty Articles and Other Publications. Paper 146. http://scholarship.law.uc.edu/fac_pubs/146 This Article is brought to you for free and open access by the Faculty Scholarship at University of Cincinnati College of Law Scholarship and Publications. It has been accepted for inclusion in Faculty Articles and Other Publications by an authorized administrator of University of Cincinnati College of Law Scholarship and Publications. For more information, please contact [email protected]. Harvard Journal ofLaw & Technology Volume 20, Number 1 Fall 2006 DIGITAL RIGHTS MANAGEMENT AND THE PROCESS OF FAIR USE Timothy K. Armstrong* TABLE OF CONTENTS I. INTRODUCTION: LEGAL AND TECHNOLOGICAL PROTECTIONS FOR FAIR USE OF COPYRIGHTED WORKS ........................................ 50 II. COPYRIGHT LAW AND/OR DIGITAL RIGHTS MANAGEMENT .......... 56 A. Traditional Copyright: The Normative Baseline ........................ 56 B. Contemporary Copyright: DRM as a "Speedbump" to Slow Mass Infringement .......................................................... -
Crowdsourcing: Today and Tomorrow
Crowdsourcing: Today and Tomorrow An Interactive Qualifying Project Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Degree of Bachelor of Science by Fangwen Yuan Jun Liang Zhaokun Xue Approved Professor Sonia Chernova Advisor 1 Abstract This project focuses on crowdsourcing, the practice of outsourcing activities that are traditionally performed by a small group of professionals to an unknown, large community of individuals. Our study examines how crowdsourcing has become an important form of labor organization, what major forms of crowdsourcing exist currently, and which trends of crowdsourcing will have potential impacts on the society in the future. The study is conducted through literature study on the derivation and development of crowdsourcing, through examination on current major crowdsourcing platforms, and through surveys and interviews with crowdsourcing participants on their experiences and motivations. 2 Table of Contents Chapter 1 Introduction ................................................................................................................................. 8 1.1 Definition of Crowdsourcing ............................................................................................................... 8 1.2 Research Motivation ........................................................................................................................... 8 1.3 Research Objectives ........................................................................................................................... -
Report to the President: MIT and the Prosecution of Aaron Swartz
Report to the President MIT and the Prosecution of Aaron Swartz Review Panel Harold Abelson Peter A. Diamond Andrew Grosso Douglas W. Pfeiffer (support) July 26, 2013 © Copyright 2013, Massachusetts Institute of Technology This worK is licensed under a Creative Commons Attribution 3.0 Unported License. PRESIDENT REIF’S CHARGE TO HAL ABELSON | iii L. Rafael Reif, President 77 Massachusetts Avenue, Building 3-208 Cambridge, MA 02139-4307 U.S.A. Phone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
RSC Policy Brief: Three Myths About Copyright Law and Where to Start to Fix It
RSC Policy Brief: Three Myths about Copyright Law and Where to Start to Fix it: November 16, 2012 RSC Staff Contact: Derek S. Khanna, [email protected], (202) 226-0718 This paper will analyze current US Copyright Law by examining three myths on copyright law and possible reforms to copyright law that will lead to more economic development for the private sector and to a copyright law that is more firmly based upon constitutional principles. 1. The purpose of copyright is to compensate the creator of the content: It’s a common misperception that the Constitution enables our current legal regime of copyright protection – in fact, it does not. The Constitution’s clause on Copyright and patents states: “To promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries;” (Article I, Section 8, Clause 8) Thus, according to the Constitution, the overriding purpose of the copyright system is to “promote the progress of science and useful arts.” In today’s terminology we may say that the purpose is to lead to maximum productivity and innovation. This is a major distinction, because most legislative discussions on this topic, particularly during the extension of the copyright term, are not premised upon what is in the public good or what will promote the most productivity and innovation, but rather what the content creators “deserve” or are “entitled to” by virtue of their creation. This lexicon is appropriate in the realm of taxation and sometimes in the realm of trade protection, but it is inappropriate in the realm of patents and copyrights. -
Frequently Asked Questions About Rcpp
Frequently Asked Questions about Rcpp Dirk Eddelbuettel Romain François Rcpp version 0.12.7 as of September 4, 2016 Abstract This document attempts to answer the most Frequently Asked Questions (FAQ) regarding the Rcpp (Eddelbuettel, François, Allaire, Ushey, Kou, Chambers, and Bates, 2016a; Eddelbuettel and François, 2011; Eddelbuettel, 2013) package. Contents 1 Getting started 2 1.1 How do I get started ?.....................................................2 1.2 What do I need ?........................................................2 1.3 What compiler can I use ?...................................................3 1.4 What other packages are useful ?..............................................3 1.5 What licenses can I choose for my code?..........................................3 2 Compiling and Linking 4 2.1 How do I use Rcpp in my package ?............................................4 2.2 How do I quickly prototype my code?............................................4 2.2.1 Using inline.......................................................4 2.2.2 Using Rcpp Attributes.................................................4 2.3 How do I convert my prototyped code to a package ?..................................5 2.4 How do I quickly prototype my code in a package?...................................5 2.5 But I want to compile my code with R CMD SHLIB !...................................5 2.6 But R CMD SHLIB still does not work !...........................................6 2.7 What about LinkingTo ?...................................................6 -
Creative Commons Niki
Creative Commons Creative Commons History Lawrence Lessig Hal Abelson Copyright Copyleft How to get a license The 4 Elements of a CC License Freedom of Information Brands/Companies That Have Used CC Criticism of Creative Commons Creative Commons History: Creative Commons was founded in 2011 as “a nonprofit organization” (page 1) which aimed to “promote an expansion of copyright law to allow greater access, use, and repurposing of creative works.” (page 1) In 2005, the organisation expanded their licensing to include scientific works which they called Science Commons[1] (page 1). Creative Commons was originally focused on U.S copyright, but since then has “expanded its licenses to be compatible with copyright laws in more than 50 countries.” (page 1) What they offer are “licenses that can be applied by copyright owners to their work to allow or prohibit certain uses.” (page 1) Dowling, John D.H. “Creative Commons.” Encyclopaedia of Social Movement Media(2011): 1-3. SAGE Knowledge, 01 Dec. 2010. Web. Lawrence Lessig Creative Commons has three original founders, one being “Lawrence Lessig, a Stanford intellectual property scholar”[1], who is also the “founder of its Centre for Internet and Society” [2]. His motivations behind creating and chairing Creative Commons is based around his belief that “recent developments in intellectual property law are moving us as a society away from freedom (especially the freedom to spread ideas that our new technologies can allow) toward greater control.” [1] Furthermore, he champions the belief that creators should assert their right not only to protect their works, but allowed them to be shared with less restrictions[1]. -
Open-Source Practices for Music Signal Processing Research Recommendations for Transparent, Sustainable, and Reproducible Audio Research
MUSIC SIGNAL PROCESSING Brian McFee, Jong Wook Kim, Mark Cartwright, Justin Salamon, Rachel Bittner, and Juan Pablo Bello Open-Source Practices for Music Signal Processing Research Recommendations for transparent, sustainable, and reproducible audio research n the early years of music information retrieval (MIR), research problems were often centered around conceptually simple Itasks, and methods were evaluated on small, idealized data sets. A canonical example of this is genre recognition—i.e., Which one of n genres describes this song?—which was often evaluated on the GTZAN data set (1,000 musical excerpts balanced across ten genres) [1]. As task definitions were simple, so too were signal analysis pipelines, which often derived from methods for speech processing and recognition and typically consisted of simple methods for feature extraction, statistical modeling, and evalua- tion. When describing a research system, the expected level of detail was superficial: it was sufficient to state, e.g., the number of mel-frequency cepstral coefficients used, the statistical model (e.g., a Gaussian mixture model), the choice of data set, and the evaluation criteria, without stating the underlying software depen- dencies or implementation details. Because of an increased abun- dance of methods, the proliferation of software toolkits, the explo- sion of machine learning, and a focus shift toward more realistic problem settings, modern research systems are substantially more complex than their predecessors. Modern MIR researchers must pay careful attention to detail when processing metadata, imple- menting evaluation criteria, and disseminating results. Reproducibility and Complexity in MIR The common practice in MIR research has been to publish find- ©ISTOCKPHOTO.COM/TRAFFIC_ANALYZER ings when a novel variation of some system component (such as the feature representation or statistical model) led to an increase in performance. -
Open Source in the Enterprise
Open Source in the Enterprise Andy Oram and Zaheda Bhorat Beijing Boston Farnham Sebastopol Tokyo Open Source in the Enterprise by Andy Oram and Zaheda Bhorat Copyright © 2018 O’Reilly Media. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online edi‐ tions are also available for most titles (http://oreilly.com/safari). For more information, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Editor: Michele Cronin Interior Designer: David Futato Production Editor: Kristen Brown Cover Designer: Karen Montgomery Copyeditor: Octal Publishing Services, Inc. July 2018: First Edition Revision History for the First Edition 2018-06-18: First Release The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Open Source in the Enterprise, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. The views expressed in this work are those of the authors, and do not represent the publisher’s views. While the publisher and the authors have used good faith efforts to ensure that the informa‐ tion and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights. -
Revolution R Enterprise™ 7.1 Getting Started Guide
Revolution R Enterprise™ 7.1 Getting Started Guide The correct bibliographic citation for this manual is as follows: Revolution Analytics, Inc. 2014. Revolution R Enterprise 7.1 Getting Started Guide. Revolution Analytics, Inc., Mountain View, CA. Revolution R Enterprise 7.1 Getting Started Guide Copyright © 2014 Revolution Analytics, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of Revolution Analytics. U.S. Government Restricted Rights Notice: Use, duplication, or disclosure of this software and related documentation by the Government is subject to restrictions as set forth in subdivision (c) (1) (ii) of The Rights in Technical Data and Computer Software clause at 52.227-7013. Revolution R, Revolution R Enterprise, RPE, RevoScaleR, RevoDeployR, RevoTreeView, and Revolution Analytics are trademarks of Revolution Analytics. Other product names mentioned herein are used for identification purposes only and may be trademarks of their respective owners. Revolution Analytics. 2570 W. El Camino Real Suite 222 Mountain View, CA 94040 USA. Revised on March 3, 2014 We want our documentation to be useful, and we want it to address your needs. If you have comments on this or any Revolution document, send e-mail to [email protected]. We’d love to hear from you. Contents Chapter 1. What Is Revolution R Enterprise? .................................................................... -
10 Pitfalls of Open Source CMS. Customer and Web Developer Perspectives
White Paper 10 Pitfalls of Open Source CMS. Customer and Web Developer Perspectives. INSIDE INTRODUCTION 2 PITFALLS? WHAT PITFALLS? 3 Demystifying the vendor 3 lock-in «Free» Doesn’t Mean 4 «No Cost» Reinventing The Wheel 6 EXECUTIVE SUMMARY Questionable Usability 7 9 Security: You Can’t Be Free open source software is highly-publicized as a cost-effective alterna- Too Careful These Days tive to proprietary software, delivering value in flexibility and true ownership. Support That Cuts 10 However, software customers should take into consideration a number of Both Ways factors that diminish this concept’s ability to meet real-life business require- A Highly Competitive 11 ments. The ten crucial open source CMS pitfalls overviewed in this white Market paper emphasize the advantages of hybrid licensed software – an alternative Medium And Large Enter- 12 software licensing approach that successfully combines the assurance of prise Market Prejudice pure proprietary solutions and openness of open source solutions. As a re- sult, hybrid licensed software allows web development companies to reduce Platform Dependence 12 web projects’ costs and time-to-market, while delivering more user-friendly The Legal Complications 13 and secure business applications to customers. HYBRID-LICENSED CMS: 14 WHAT’S IN A NAME? This white paper has tweetable references. To tweet the content ABOUT BITRIX 16 simply click the tweet button wherever it appears 2 10 Pitfalls of Open Source CMS. Web Developers and Customers Perspective. INTRODUCTION According to W3Techs1 approximately 90 percent of Alexa’s 1,000,000 top- ranked websites are running WordPress, Joomla!, Drupal, TYPO3 or other The content management highly-publicized open source CMS products.