This presentation looks at issues surrounding the licensing of research data for reuse. It outlines the concepts behind data licensing, looks at data reuse licenses used by CESSDA data archives, considers the role of Creative Commons and Open Data Licenses in sharing social science research data, and highlights some of the problems, issues, and challenges facing archives and repositories.
Open Data Institute Course - Open Data in a Day conducted by Registered ODI Trainer Ian Henshaw on October 14, 2015 in RTP, NC USA - Deck #2 to Open Data Licensing, Law and Best Practice
This document discusses electronic discovery (eDiscovery) which refers to the discovery of electronically stored information in legal cases. It notes that eDiscovery costs are skyrocketing, averaging over $1.5 million per corporate lawsuit. The document outlines typical eDiscovery costs including collecting, processing, reviewing data which can cost thousands or millions depending on the size of the case. It emphasizes that proactive information management is key to addressing eDiscovery by developing policies to help employees manage information and only retain necessary records.
Most businesses have valuable databases of information, such as client lists, customer lists, lists of prospects – as well as data about products, materials, financial, insurance and other information.
The introduction of GDPR has led more businesses to think about what rights they have in their data and in their databases. This area of law has changed significantly in recent years as a result of court decisions across Europe.
This short webinar provides you with the key information you need to identify, develop and protect these rights.
DEFCON17 - Your Mind: Legal Status, Rights and Securing YourselfJames Arlen
James Arlen and Tiffany Rad
As a participant in the information economy, you no longer exclusively own material originating from your organic brain; you leave a digital trail with your portable device's transmitted communications and when your image is captured by surveillance cameras. Likewise, if you Tweet or blog, you have outsourced a large portion of your memory and some of your active cognition to inorganic systems. U.S. and International laws relating to protection of intellectual property and criminal search and seizure procedures puts into question protections of these ephemeral communications and memoranda stored on your personal computing devices, in cloud computing networks, on off-shore "subpoena proof" server platforms, or on social networking sites.
Although once considered to be futuristic technologies, as we move our ideas and memories onto external devices or are subjected to public surveillance with technology (Future Attribute Screening Technology) that assesses pre-crime thoughts by remotely measuring biometric data such as heart rate, body temperature, pheromone responses, and respiration, where do our personal privacy rights to our thoughts end and, instead, become public expressions with lesser legal protections? Similarly, at what state does data in-transit or stored in implantable medical devices continuously connected to the Internet become searchable? In a society in which there is little differentiation remaining between self/computer, thoughts/stored memoranda, and international boundaries, a technology lawyer/computer science professor and a security professional will recommend propositions to protect your data and yourself.
Data Sharing and the Polar Information CommonsKaitlin Thaney
1. The document discusses challenges with applying traditional copyright licenses to data and proposes establishing norms rather than licenses to govern data sharing.
2. It suggests norms that promote open, accessible, and interoperable data by waiving all rights necessary for data extraction and reuse, while encouraging attribution and quality standards through terms of use rather than legal requirements.
3. The document argues that data should flow freely in an open infrastructure to support new uses and insights, and that data has more value when structured and annotated within such a system rather than treated as a private property.
E Discovery General E Discovery Presentationjvanacour
This document provides an overview of key concepts and best practices regarding electronic discovery (e-discovery). It discusses the duty to preserve relevant evidence once litigation is reasonably anticipated. It also outlines the stages of managing e-discovery, including having a reasonable document retention policy prior to notice, issuing a litigation hold once notice is received, and complying with discovery requests once litigation begins. The document emphasizes communicating preservation obligations, overseeing preservation efforts, and producing electronic documents and metadata in a usable format.
Total Evidence Management (TEM) is an approach to efficiently manage both digital and physical evidence for complex litigation in the digital age. TEM combines all relevant evidence, including documents, emails, audio/video files, and metadata from various sources into a centralized electronic repository. This repository allows lawyers to preserve, process, review, analyze, organize and collaborate on evidence. By using TEM, lawyers can save clients time and money in the discovery process where most cases are won or lost, rather than during the courtroom trial.
Open Data Institute Course - Open Data in a Day conducted by Registered ODI Trainer Ian Henshaw on October 14, 2015 in RTP, NC USA - Deck #2 to Open Data Licensing, Law and Best Practice
This document discusses electronic discovery (eDiscovery) which refers to the discovery of electronically stored information in legal cases. It notes that eDiscovery costs are skyrocketing, averaging over $1.5 million per corporate lawsuit. The document outlines typical eDiscovery costs including collecting, processing, reviewing data which can cost thousands or millions depending on the size of the case. It emphasizes that proactive information management is key to addressing eDiscovery by developing policies to help employees manage information and only retain necessary records.
Most businesses have valuable databases of information, such as client lists, customer lists, lists of prospects – as well as data about products, materials, financial, insurance and other information.
The introduction of GDPR has led more businesses to think about what rights they have in their data and in their databases. This area of law has changed significantly in recent years as a result of court decisions across Europe.
This short webinar provides you with the key information you need to identify, develop and protect these rights.
DEFCON17 - Your Mind: Legal Status, Rights and Securing YourselfJames Arlen
James Arlen and Tiffany Rad
As a participant in the information economy, you no longer exclusively own material originating from your organic brain; you leave a digital trail with your portable device's transmitted communications and when your image is captured by surveillance cameras. Likewise, if you Tweet or blog, you have outsourced a large portion of your memory and some of your active cognition to inorganic systems. U.S. and International laws relating to protection of intellectual property and criminal search and seizure procedures puts into question protections of these ephemeral communications and memoranda stored on your personal computing devices, in cloud computing networks, on off-shore "subpoena proof" server platforms, or on social networking sites.
Although once considered to be futuristic technologies, as we move our ideas and memories onto external devices or are subjected to public surveillance with technology (Future Attribute Screening Technology) that assesses pre-crime thoughts by remotely measuring biometric data such as heart rate, body temperature, pheromone responses, and respiration, where do our personal privacy rights to our thoughts end and, instead, become public expressions with lesser legal protections? Similarly, at what state does data in-transit or stored in implantable medical devices continuously connected to the Internet become searchable? In a society in which there is little differentiation remaining between self/computer, thoughts/stored memoranda, and international boundaries, a technology lawyer/computer science professor and a security professional will recommend propositions to protect your data and yourself.
Data Sharing and the Polar Information CommonsKaitlin Thaney
1. The document discusses challenges with applying traditional copyright licenses to data and proposes establishing norms rather than licenses to govern data sharing.
2. It suggests norms that promote open, accessible, and interoperable data by waiving all rights necessary for data extraction and reuse, while encouraging attribution and quality standards through terms of use rather than legal requirements.
3. The document argues that data should flow freely in an open infrastructure to support new uses and insights, and that data has more value when structured and annotated within such a system rather than treated as a private property.
E Discovery General E Discovery Presentationjvanacour
This document provides an overview of key concepts and best practices regarding electronic discovery (e-discovery). It discusses the duty to preserve relevant evidence once litigation is reasonably anticipated. It also outlines the stages of managing e-discovery, including having a reasonable document retention policy prior to notice, issuing a litigation hold once notice is received, and complying with discovery requests once litigation begins. The document emphasizes communicating preservation obligations, overseeing preservation efforts, and producing electronic documents and metadata in a usable format.
Total Evidence Management (TEM) is an approach to efficiently manage both digital and physical evidence for complex litigation in the digital age. TEM combines all relevant evidence, including documents, emails, audio/video files, and metadata from various sources into a centralized electronic repository. This repository allows lawyers to preserve, process, review, analyze, organize and collaborate on evidence. By using TEM, lawyers can save clients time and money in the discovery process where most cases are won or lost, rather than during the courtroom trial.
This document discusses Creative Commons (CC) and its role in open access publishing. CC provides free copyright licenses that allow authors to select how their works can be shared, reused and remixed. The definition of open access implies works should be freely available online without financial, legal or technical barriers. CC licenses and RDFa can encode copyright information and metadata in works to indicate how they can be accessed and used. CC is developing new tools to help identify works in the public domain and support reproducible research by recommending appropriate licensing for related works, code and data.
The document discusses the growth of electronic data and its impact on e-discovery in litigation. It notes that e-discovery cases and sanctions are on the rise as data volumes grow exponentially. Various judges weigh in on parties' obligations around e-discovery and the consequences for failing to meet those obligations. The use of cloud computing and managed services is presented as a way for law firms to more efficiently handle e-discovery. The document concludes by emphasizing the need for a coordinated approach and proper resources to successfully manage e-discovery.
This document provides an overview of digital forensics. It discusses how data is stored on hard drives in allocated and unallocated space, including file slack and slack space. It describes the three types of digital evidence as active data, latent data, and archival data. It also explains key concepts such as file systems, operating systems, file allocation tables, and how deleting files works at the logical level. The goal is to educate legal professionals on understanding digital evidence and the process of computer forensics examinations.
This document discusses electronic discovery (e-discovery) and the evolution of technology and legal demands in the 21st century. It defines e-discovery and electronically stored information (ESI), outlines the common forms and sources of ESI, and describes the stages of the electronic discovery reference model including identification, preservation, collection, processing, review, analysis, and production. It emphasizes the importance of preservation in e-discovery and explains why e-discovery problems involving volume and sources of electronic information are challenging. Finally, it pitches partnering with Pye Legal for e-discovery solutions that contain costs, reduce risks, and avoid sanctions.
Cyber Summit 2016: Privacy Issues in Big Data Sharing and ReuseCybera Inc.
This document summarizes a presentation on big data and data reuse given by Bart Custers. It discusses:
1) The Eudeco project which examines big data and data reuse from legal, societal, economic, and technological perspectives across multiple European countries.
2) Issues with data sharing and reuse, including potential privacy violations, discrimination, lack of transparency, and unintended consequences from new uses of data or placing it in new contexts.
3) Potential solutions discussed, including privacy impact assessments, privacy by design, and new approaches focusing more on transparency and responsibility than restricting data access and use.
Data Minimization.Defensible Culling Techniques 04.03.09knugent
The document discusses data minimization techniques for reducing costs in electronic discovery. It outlines 5 steps to data minimization including filtering by file type and date, removing system/program files, deduplication, keyword filtering, and advanced analytics. The document also notes that utilizing these strategies can reduce collected data volumes by 40-80%, allowing cases to be assessed virtually as soon as data is collected and lowering processing costs. It promotes the use of transparent search technologies to ensure discovery searches are defensible.
The open semantic enterprise enterprise data meets web dataGeorg Guentner
Presentation in workshop at the 2nd B2B Software Days (11.04.2013, Vienna), together with Herbert Beilschmidt (Oracle Austria):
The Open Semantic Enterprise.Enterprise Data meets Web Data.
The technologies of the “Web od Data” have reached a degree of maturity and acceptance allowing the productive use in enterprises for the support of their business processes. Though the focus is currently on the adoption and use of Open (Linked) Data, the underlying principles can also be applied to the closed data sources and proprietary data structures usually available in enterprises.
The workshop outlines the conceptual and architectural approaches to open enterprise data sources and interweave them with the Web of Data. It shows concrete application scenarios of an open source “semantic toolset” that can be integrated with enterprise information and content management systems to open data silos, establish a layer of adaptive integrated views of the enterprise information and support decision processes thus paving the way to an “open semantic enterprise”.
The topical semantic toolset for enterprise content integration includes Apache Stanbol (knowledge extraction), Apache Marmotta (Linked Data Platform), the Linked Media Framework (networked knowledge) und VIE (interactive knowledge).
State-of-the-art big data platforms need to process massive quantities of data in batch and in parallel - filtering, transforming and sorting it before loading it into an enterprise data warehouse. In order to realize an Open Semantic Enterprise, a big data platform has to be optimized for acquiring, organizing, and loading unstructured data. Technological approaches such as NoSQL databases and connectors for Apache Hadoop complement big data solutions for the open world of a semantic enterprise.
“Who’s Afraid of E-Discovery” was presented by George E. Pallas and Jason Copley from the Law Firm of Cohen Seglias Pallas Greenhall & Fuman PC for the members of the Mid-Atlantic Steel Fabricators Association.
Hadoop World 2011: The Hadoop Award for Government Excellence - Bob Gourley -...Cloudera, Inc.
Federal, State and Local governments and the development community surrounding them are busy creating solutions leveraging the Apache Foundation Hadoop capabilities. This session will highlight the top five solutions selected by an all star panel of judges. Who will take home the coveted Hadoop Award for Government Excellence (Haggie) Nominations for Haggies are being accepted now at http://CTOlabs.com
Creative Commons Law and the GeoWeb presentationCreative Commons
1) Creative Commons licenses can be used for open geodata and databases as copyright law treats data and content similarly.
2) Good design principles are important for open data, and Creative Commons licenses keep things simple without imposing extra restrictions.
3) Creative Commons is beginning the process for a new version 4.0 license and is seeking feedback from the open geodata community on issues like non-copyright database rights and growing an interoperable open data commons.
SPIF - Sensitive and Private Information Filterbirhanum
The document describes a proposed Sensitive and Private Information Filter (SPIF) to allow individuals and organizations to publish open data while filtering out sensitive private information. It notes the need to support common file formats, filter identifiers like social security numbers and credit cards, and provide specific details on what was removed. The proposed solution is an application that can filter such private information from text, spreadsheet, document and other file types while retaining the overall content for public release.
The document discusses issues around data protection and privacy in a world of global data sharing, particularly in the context of scientific research. It outlines challenges like determining data ownership and control when data is shared globally online. It also summarizes key concepts and principles from the European Union's data protection directive, including rules around transferring personal data outside of the EU. Potential solutions discussed include revising the EU directive to better accommodate open data and scientific research.
Using Open Science to advance science - advancing open data Robert Oostenveld
This document discusses using open science practices like open data to advance science. It notes the benefits of open data like improved reproducibility and opportunities for data mining. However, sharing neuroimaging and other human subject data presents challenges regarding data size, sensitivity, and privacy regulations. The document promotes using the Brain Imaging Data Structure (BIDS) format to organize data in an open, standardized way. It also discusses the gradient between personal/identifiable data that requires protection and de-identified research data that can be shared, as well as legal constraints and appropriate repositories for sharing data responsibly.
This presentation was provided by Melissa Levine of the University of Michigan during a NISO Virtual Conference on the topic of data curation, held on Wednesday, August 31, 2016
CuttingEEG - Open Science, Open Data and BIDS for EEGRobert Oostenveld
Starting with education, inception of research questions, planning, acquisition, analysis and reporting, there are multiple points where Open Science should play a role. In my presentation at the CuttingEEG conference in Paris, I argue that we should not only be sharing primary outcomes as Open Access publications, but that openness involves the full research cycle. Specifically, I will be sharing my experience with Open Data, privacy challenges and possibilities under the GDPR, Open Source for sharing analysis methods, dealing with imperfections in science and versioning of data, code and results. Finally, I will introduce BIDS for EEG, a new effort to increase the impact of shared and well-documented EEG data.
The document discusses several reputable sources for finding reliable datasets for academic research, including research data repositories like Mendeley Data, Dryad Digital Repository, and Harvard Dataverse. It provides details on the types of data available and fields covered for repositories like LCAS, Nasdaq Data Link, figshare, and Network Repository. The document emphasizes ensuring compliance with terms of use and applicable laws when using datasets from these resources.
Sustainable Legal Framework for Open Access to Research Datagideon christian
The document discusses frameworks for open access to research data through information and communication technologies. It covers data rights in the US and EU, examples of open data frameworks like Creative Commons licenses, and ethical issues around privacy and consent. Trends in open data access across science and social science databases are examined, with only a few providing full open access. Further research questions around determining appropriate access frameworks and the relationship between openness and data utility are also outlined.
This document discusses Creative Commons (CC) and its role in open access publishing. CC provides free copyright licenses that allow authors to select how their works can be shared, reused and remixed. The definition of open access implies works should be freely available online without financial, legal or technical barriers. CC licenses and RDFa can encode copyright information and metadata in works to indicate how they can be accessed and used. CC is developing new tools to help identify works in the public domain and support reproducible research by recommending appropriate licensing for related works, code and data.
The document discusses the growth of electronic data and its impact on e-discovery in litigation. It notes that e-discovery cases and sanctions are on the rise as data volumes grow exponentially. Various judges weigh in on parties' obligations around e-discovery and the consequences for failing to meet those obligations. The use of cloud computing and managed services is presented as a way for law firms to more efficiently handle e-discovery. The document concludes by emphasizing the need for a coordinated approach and proper resources to successfully manage e-discovery.
This document provides an overview of digital forensics. It discusses how data is stored on hard drives in allocated and unallocated space, including file slack and slack space. It describes the three types of digital evidence as active data, latent data, and archival data. It also explains key concepts such as file systems, operating systems, file allocation tables, and how deleting files works at the logical level. The goal is to educate legal professionals on understanding digital evidence and the process of computer forensics examinations.
This document discusses electronic discovery (e-discovery) and the evolution of technology and legal demands in the 21st century. It defines e-discovery and electronically stored information (ESI), outlines the common forms and sources of ESI, and describes the stages of the electronic discovery reference model including identification, preservation, collection, processing, review, analysis, and production. It emphasizes the importance of preservation in e-discovery and explains why e-discovery problems involving volume and sources of electronic information are challenging. Finally, it pitches partnering with Pye Legal for e-discovery solutions that contain costs, reduce risks, and avoid sanctions.
Cyber Summit 2016: Privacy Issues in Big Data Sharing and ReuseCybera Inc.
This document summarizes a presentation on big data and data reuse given by Bart Custers. It discusses:
1) The Eudeco project which examines big data and data reuse from legal, societal, economic, and technological perspectives across multiple European countries.
2) Issues with data sharing and reuse, including potential privacy violations, discrimination, lack of transparency, and unintended consequences from new uses of data or placing it in new contexts.
3) Potential solutions discussed, including privacy impact assessments, privacy by design, and new approaches focusing more on transparency and responsibility than restricting data access and use.
Data Minimization.Defensible Culling Techniques 04.03.09knugent
The document discusses data minimization techniques for reducing costs in electronic discovery. It outlines 5 steps to data minimization including filtering by file type and date, removing system/program files, deduplication, keyword filtering, and advanced analytics. The document also notes that utilizing these strategies can reduce collected data volumes by 40-80%, allowing cases to be assessed virtually as soon as data is collected and lowering processing costs. It promotes the use of transparent search technologies to ensure discovery searches are defensible.
The open semantic enterprise enterprise data meets web dataGeorg Guentner
Presentation in workshop at the 2nd B2B Software Days (11.04.2013, Vienna), together with Herbert Beilschmidt (Oracle Austria):
The Open Semantic Enterprise.Enterprise Data meets Web Data.
The technologies of the “Web od Data” have reached a degree of maturity and acceptance allowing the productive use in enterprises for the support of their business processes. Though the focus is currently on the adoption and use of Open (Linked) Data, the underlying principles can also be applied to the closed data sources and proprietary data structures usually available in enterprises.
The workshop outlines the conceptual and architectural approaches to open enterprise data sources and interweave them with the Web of Data. It shows concrete application scenarios of an open source “semantic toolset” that can be integrated with enterprise information and content management systems to open data silos, establish a layer of adaptive integrated views of the enterprise information and support decision processes thus paving the way to an “open semantic enterprise”.
The topical semantic toolset for enterprise content integration includes Apache Stanbol (knowledge extraction), Apache Marmotta (Linked Data Platform), the Linked Media Framework (networked knowledge) und VIE (interactive knowledge).
State-of-the-art big data platforms need to process massive quantities of data in batch and in parallel - filtering, transforming and sorting it before loading it into an enterprise data warehouse. In order to realize an Open Semantic Enterprise, a big data platform has to be optimized for acquiring, organizing, and loading unstructured data. Technological approaches such as NoSQL databases and connectors for Apache Hadoop complement big data solutions for the open world of a semantic enterprise.
“Who’s Afraid of E-Discovery” was presented by George E. Pallas and Jason Copley from the Law Firm of Cohen Seglias Pallas Greenhall & Fuman PC for the members of the Mid-Atlantic Steel Fabricators Association.
Hadoop World 2011: The Hadoop Award for Government Excellence - Bob Gourley -...Cloudera, Inc.
Federal, State and Local governments and the development community surrounding them are busy creating solutions leveraging the Apache Foundation Hadoop capabilities. This session will highlight the top five solutions selected by an all star panel of judges. Who will take home the coveted Hadoop Award for Government Excellence (Haggie) Nominations for Haggies are being accepted now at http://CTOlabs.com
Creative Commons Law and the GeoWeb presentationCreative Commons
1) Creative Commons licenses can be used for open geodata and databases as copyright law treats data and content similarly.
2) Good design principles are important for open data, and Creative Commons licenses keep things simple without imposing extra restrictions.
3) Creative Commons is beginning the process for a new version 4.0 license and is seeking feedback from the open geodata community on issues like non-copyright database rights and growing an interoperable open data commons.
SPIF - Sensitive and Private Information Filterbirhanum
The document describes a proposed Sensitive and Private Information Filter (SPIF) to allow individuals and organizations to publish open data while filtering out sensitive private information. It notes the need to support common file formats, filter identifiers like social security numbers and credit cards, and provide specific details on what was removed. The proposed solution is an application that can filter such private information from text, spreadsheet, document and other file types while retaining the overall content for public release.
The document discusses issues around data protection and privacy in a world of global data sharing, particularly in the context of scientific research. It outlines challenges like determining data ownership and control when data is shared globally online. It also summarizes key concepts and principles from the European Union's data protection directive, including rules around transferring personal data outside of the EU. Potential solutions discussed include revising the EU directive to better accommodate open data and scientific research.
Using Open Science to advance science - advancing open data Robert Oostenveld
This document discusses using open science practices like open data to advance science. It notes the benefits of open data like improved reproducibility and opportunities for data mining. However, sharing neuroimaging and other human subject data presents challenges regarding data size, sensitivity, and privacy regulations. The document promotes using the Brain Imaging Data Structure (BIDS) format to organize data in an open, standardized way. It also discusses the gradient between personal/identifiable data that requires protection and de-identified research data that can be shared, as well as legal constraints and appropriate repositories for sharing data responsibly.
This presentation was provided by Melissa Levine of the University of Michigan during a NISO Virtual Conference on the topic of data curation, held on Wednesday, August 31, 2016
CuttingEEG - Open Science, Open Data and BIDS for EEGRobert Oostenveld
Starting with education, inception of research questions, planning, acquisition, analysis and reporting, there are multiple points where Open Science should play a role. In my presentation at the CuttingEEG conference in Paris, I argue that we should not only be sharing primary outcomes as Open Access publications, but that openness involves the full research cycle. Specifically, I will be sharing my experience with Open Data, privacy challenges and possibilities under the GDPR, Open Source for sharing analysis methods, dealing with imperfections in science and versioning of data, code and results. Finally, I will introduce BIDS for EEG, a new effort to increase the impact of shared and well-documented EEG data.
The document discusses several reputable sources for finding reliable datasets for academic research, including research data repositories like Mendeley Data, Dryad Digital Repository, and Harvard Dataverse. It provides details on the types of data available and fields covered for repositories like LCAS, Nasdaq Data Link, figshare, and Network Repository. The document emphasizes ensuring compliance with terms of use and applicable laws when using datasets from these resources.
Sustainable Legal Framework for Open Access to Research Datagideon christian
The document discusses frameworks for open access to research data through information and communication technologies. It covers data rights in the US and EU, examples of open data frameworks like Creative Commons licenses, and ethical issues around privacy and consent. Trends in open data access across science and social science databases are examined, with only a few providing full open access. Further research questions around determining appropriate access frameworks and the relationship between openness and data utility are also outlined.
Scholarship in a connected world: New ways to know, new ways to showDerek Keats
The document discusses how libraries and scholarship are changing in a digital world of abundance rather than scarcity. It covers four key areas: ubiquitous computing, the social academic, research data, and free and open versus secret science. The author argues that libraries must adapt to this new environment by embracing new technologies, facilitating social and open sharing of knowledge, helping with research data management, and promoting open access over secret science.
This document discusses legal and ethical issues related to data sharing. It covers rights and copyright regarding data, how to address ethics when sharing personal data under GDPR, and obtaining consent from participants. Guidelines are provided for discovering and accessing shared data from repositories. Questions about data sharing are welcomed.
New challenges for digital scholarship and curation in the era of ubiquitous ...Derek Keats
A keynote presentation that I gave at the The 4th African Digital Scholarship and Curation Conference (see: http://www.nedicc.ac.za/test/Programme.aspx) on 16 May 2011.
This is a presentation delivered on December 1, 2020 by the UC Berkeley Library's Office of Scholarly Communication Services and the Research Data Management Program.
Are you unsure about how you can use or reuse other people’s data in your teaching or research, and what the terms and conditions are? Do you want to share your data with other researchers or license it for reuse but are wondering how and if that’s allowed? Do you have questions about university or granting agency data ownership and sharing policies, rights, and obligations? We will provide clear guidance on all of these questions and more in this interactive webinar on the ins-and-outs of data sharing and publishing.
- Explore venues and platforms for sharing and publishing data
- Unpack the terms of contracts and licenses affecting data reuse, sharing, and publishing
- Help you understand how copyright does (and does not) affect what you can do with the data you create or wish to use from other people
- Consider how to license your data for maximum downstream impact and reuse
- Demystify data ownership and publishing rights and obligations under university and grant policies
The Linked Data Research Centre (LiDRC) is a new effort within DERI to advance linked data research and development. The LiDRC operates across existing units and has 11 DERI researchers working with 9 international peers. Its research themes include publishing, discovery, application domains, and streamed linked data. The LiDRC contributes linked data infrastructure, provides tools and libraries, and participates in standards activities. It is calling for input on a technical report about linked data applications.
This document summarizes a thesis defense presentation on a conceptual model for a public commons for geospatial data. The presentation introduces the objectives of making it easier for creators to share spatial data by providing mechanisms for metadata creation, attribution and credit recognition, liability protection, and non-monetary benefits. It then describes the conceptual design of the public commons, which would use an open access licensing approach, enhanced metadata searchability, and techniques for embedding identifying information in datasets. The presentation demonstrates features of the public commons and concludes that it could incentivize thousands of individuals to share datasets by addressing impediments to sharing.
The document discusses linking building data from multiple systems using linked data principles. Building information is currently scattered across different systems for energy usage, maintenance, finance, occupancy, and more. However, effectively managing a building requires a holistic view across all this data. Linked data provides a method to expose, share, and connect building data from different systems and technologies by identifying objects with URIs and linking information with relationships. This can provide new insights by linking domains like energy and resource utilization. The challenges of data interoperability, information granularity, interpreting data, and empowering actions are also discussed. A case study of applying these approaches to link operational and sensor data from a research building is also presented.
Be open: what funders want you to do with your publications and research dataLeon Osinski
Research funders want researchers to:
1. Publish research articles through open access to make the articles widely available.
2. Deposit the underlying research data in repositories to make the data findable, accessible, interoperable, and reusable (FAIR).
3. Attach open licenses like CC BY to both publications and data to allow for commercial reuse when possible.
Presentation given at the Consorcio Madrono conference on Data Management Plans in Horizon 2020 http://www.consorciomadrono.es/info/web/blogs/formacion/217.php
Similar to A Look at CESSDA and Data Re-use Licenses (20)
„Wege in die Köpfe“ - Forschungsdatenmanagement in den
Geowissenschaften. Berlin, 3.-4. Juli 2014.
Workshop des EWIG Projekts (http://ewig.gfz-potsdam.de)
Supporting the creation, management, and long-term preservation of social sc...CESSDA Training
The document summarizes training services offered by the CESSDA Training Centre. It provides self-directed online training materials, webinars, and workshops on topics like digital preservation, research data management, and data discovery. The training is aimed at archivists, data librarians, researchers, and others working with social science data. It also offers train-the-trainer modules and assistance with writing data management plans for research proposals. The overall goal is to support the creation, management, and long-term preservation of social science research data.
Academic Writing and Research Data ManagementCESSDA Training
This document discusses academic writing standards for research data management and documentation. It provides examples of documentation from the European Values Study conducted in 1981, 1990, 1999, and 2008. The analysis found improvements over time in documenting the sample, methodology, variables, and providing references to allow other researchers to understand and replicate the work. Standards evolved as the replication movement increased, making methodology sections more transparent and data more reusable.
Alive and kicking! Keeping data re-usable in the European Values StudyCESSDA Training
Alive and kicking! Keeping data re-usable in the European Values Study
Evelyn Brislinger, Astrid Recker
GESIS - Leibniz Institute for the Social Sciences
Repeated cross-national surveys generate huge amounts of cross-linked data and metadata. To enable replication and to make this data re-usable in new research contexts, thorough and standardized documentation of data and project workflow is indispensable. However, in the social sciences, data and documentation often undergo a continuous process of correction, refinement, and further development. These processes need to be documented too, especially to allow data providers to build on these results and experiences in preparation of the next wave.
In this paper, we use the European Values Study (EVS) 1981-2008 to illustrate the challenges to be met in the active curation of extensive amounts of data and documentation created, altered, and re-used across the survey life-cycle. Outlining how these challenges are met by the EVS, we will particularly discuss the following questions: Looking beyond the “standard” documentation of data and survey methods, what supporting contextual information should accompany data to ensure their effective “migration” and use across waves? Especially relevant in a project composed of 125 national surveys covering 49 countries and spanning almost 30 years is the question which preservation metadata is needed to achieve this objective and thus support the long-term accessibility of data and contextual information?
De-mystifying OAIS compliance Benefits and challenges of mapping the OAIS re...CESSDA Training
Natascha Schumann, GESIS-Leibniz Institute for the Social Sciences
Dr. Astrid Recker, GESIS-Leibniz Institute for the Social Sciences
Since its initial publication in 2002, the OAIS Reference Model, its concepts and terminology, have become essential to the digital preservation discourse. In this discourse, the topos – or myth – of “OAIS compliance” continues to play a central part as archives and repositories seek to demonstrate their fitness for the challenge of digital preservation. This presentation considers briefly what OAIS is (and can be used for) and what it is not – namely, an abstract reference model, but not an architecture that can be implemented directly –, and which challenges and benefits this entails.
We then use the GESIS Data Archive for the Social Sciences as an example of mapping OAIS onto an existing archival system, looking at the organizational and “technical” dimensions and exploring positive effects and benefits, as well as difficulties of completing this process. Thus, such a mapping can be taxing for an established archive: As most of the workflows have grown and proven their adequacy over a considerable period of time, taking a step back and viewing these processes from a new perspective is a challenge in itself.
Access Policies and Licensing for Archives and RepositoriesCESSDA Training
This document provides information about the DASISH project, which brings together five European social science research infrastructures to work on common activities and problems. It discusses the objectives of DASISH, which include improving data quality, data enrichment, digital preservation, and legal and ethics activities. It describes Work Package 7 on education and training, which aims to establish a joint domain for training, inspire new research approaches, and discuss the role of infrastructures in methodologies. The first DASISH training module and workshop are introduced, focusing on access policies and licensing for archives and repositories.
Archiving and Data Management Training and Information CenterCESSDA Training
The centre aims to promote excellence in research data management, archiving and preservation. It helps researchers, archives and repositories maximize the value of research data through various training workshops on topics like data planning, sharing, documentation, formats, storage, dissemination and reuse. The centre also assists with reviewing existing data sources, implementing data collection methods, and preparing data for long-term archiving and reuse.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
How to Manage Your Lost Opportunities in Odoo 17 CRM
A Look at CESSDA and Data Re-use Licenses
1. A look at CESSDA and data re-use
licenses
Laurence Horton
GESIS – Leibniz Institute for the
Social Sciences
2. A CESSDA development
• Moves towards establishing a legal entity
ERIC or its equivalent
– CESSDA-AS
• As of now, no CESSDA template or
standard for licenses
3. CESSDA
• Council of European
Social Science Data
Archives
• Established 1976
• 28 member archives
4. What is a license?
• Verb: 'give a permit to someone; allow
something’ (OED)
• We live in a world where we don’t own the
things we buy
• It’s not a contract because we don’t really
negotiate: “Take it or leave it”
5. How’s it work?
Data owner
Data service
Data re-user Data re-user Data re-user
Depositor
license
User
license
7. Q: What’s the big problem with
social science data?
• A: People.
– A strategy to protect
the identity of
participants is critical
to ethical research.
– Also to ensure
researchers receive
the credit they
deserve
8. What do we expect to see in a social
science archive license?
Depositor license
Intellectual Property That the depositor owns, or has the right from the owner(s) to
deposit the data for preservation and/or re-use
Privacy That the data does not violate confidentiality and data protection
laws
Consent That consent for re-use and/or preservation has been given or not
explicitly prevented
Ownership Clear statement on the subsequent ownership of the data and right
to disseminate
9. What do we expect to see in a social
science archive license?
Re-use license
Intellectual Property To respect the IPR of the data, not to sell or pass on the data
without permission.
Attribution To say where the data came from and credit the data owner and
disseminator in any output where it is used.
Non-responsibility To recognize that they alone are responsible for the quality of
outputs in which the data is used.
Usage Restrictions on access and use for commercial purposes.
Confidentiality To respect original consent agreements and any applicable data
protection laws.
Security Outlining steps or minimum standards for keeping data secure.
10. Comparing CESSDA archive licenses
Archive IPR Attribution Non-responsibility Usage Confidentiality Security
ADP x x x x
ADPSS x x x
SDA x x x x x
CIS x x x
DANS x x x x
DDA x x x x x
ESSDA x x x
FORS x x x x
FSD x x x x
GESIS x x x x
LiDA x x x x
Reseu x x x x
SND x x x
TARKI x x
UCD x x x x x
UKDS x x x x x
WISDOM x x x x
11. Lost in Translation, or just lost?
CIS
“Data shall always be published
together”
GESIS
“The user is obliged to quote all used
documents according to scientific
conventions”
LiDA
“acknowledge this by a reference to
THE ARCHIVE”
TARKI
“TÁRKI Databank as the publisher of
the dataset.”
UCD 4 pages long!
UKDS
“correct methods of citation and
acknowledgement in publications”
WISDOM
“Range of access from open to
closed”
12. Challenges
• These licenses all seem to be saying
(roughly) the same thing
• …but none of them say it the same way
• …and they say it at varying lengths and
with different complexity in language
14. Enforcing?
• Are we powerless to enforce licenses?
– What can we do other than rely on
(expensive, time-consuming) legal action?
– How do we deal with international violations?
15. The Gordian Knot
• How do we deal with
the intractable
problem of attribution
stacking?
– Attribution/citation
– Sharing alike
– No derivatives
16. What about Creative Commons?
• Simple, short, clear,
widely known.
• But (like most
licenses based on
IPR) not designed
for data.
17. The dream?
• Can we move to a
clear, concise standard
that doesn’t…
– Unnecessarily restrict
access
– Can absorb variations
in what constitutes
Intellectual Property
Rights
18. Final thought
“..there is only one thing in the world
worse than having a data license,
and that is not having a data
license.”
19. IPR bibliography
ADP. (n.d.). Restrictions and Terms of Use. Ljubliana: Slovenian Social Science Data Archives. Retrieved from http://www.adp.fdv.uni-
lj.si/eng/za_uporabnike/o_podatkih/
ADPSS Sociodat. (n.d.). Access Modality. Milan. Retrieved from http://www.sociologiadip.unimib.it/sociodata/eng/index.php?w=modalita
ARCES/CIS. (n.d.). Request Form. Madrid: Archivo de Estudios Sociales/Centro de Investigaciones Sociológicas. Retrieved from
http://www.cis.es/cis/opencms/EN/7_arces/impreso.html
Association of Research Libraries. (2012). Code of Best Practices in Fair Use for Academic and Research Libraries (p. 29). Retrieved from
http://www.arl.org/bm~doc/code-of-best-practices-fair-use.pdf
Australian National Data Service. (2012). Ethics, consent & data sharing. Retrieved from http://www.ands.org.au/guides/ethics-working-level.pdf
Ball, A. (2012). How to License Research Data. Edinburgh. Retrieved from http://www.dcc.ac.uk/resources/how-guides/license-research-data
Buccafusco, C. J., & Heald, P. J. (2012). Do Bad Things Happen When Works Enter the Public Domain?: Empirical Tests of Copyright Term
Extension. SSRN Electronic Journal, 50. doi:10.2139/ssrn.2130008
Centre for Intellectual Property Law. (2011). The Legal Status of Research Data in the Knowledge Exchange Partner Countries (p. 59).
Retrieved from http://www.knowledge-exchange.info/default.aspx?id=461
Centre for Intellectual Property Law. (2012a). The legal status of research data in the Netherlands (p. 35). Retrieved from
http://www.knowledge-exchange.info/default.aspx?id=461
Centre for Intellectual Property Law. (2012b). The legal status of research data in the United Kingdom (p. 29). Retrieved from
http://www.knowledge-exchange.info/default.aspx?id=461
20. IPR bibliography
Centre for Intellectual Property Law. (2012c). The legal status of research data in Germany (p. 31). Retrieved from http://www.knowledge-
exchange.info/default.aspx?id=461
Centre for Intellectual Property Law. (2012d). The legal status of research data in Denmark (p. 30). Retrieved from http://www.knowledge-
exchange.info/default.aspx?id=461
CEPS. (n.d.). No Title. Luxembourg: Centre d’Études de Populations, de Pauvreté et de Politiques Socio-Economiques.
Charlesworth, A. (2012). Intellectual Property Rights for Digital Preservation (p. 50). doi:dx.doi.org/10.7207/twr12-02
DANS. (n.d.). Citing data. The Hague: Data Archiving and Networked Series. Retrieved from
http://www.dans.knaw.nl/sites/default/files/file/EASY/Frequently Asked Questions - Using data from EASY_DEF.doc
DDA. (n.d.). Requisition for data material. Odense: Dansk Data Arkiv. Retrieved from http://samfund.dda.dk/dda/dokumenter/Rek_uk.pdf
ESSDA. (n.d.). Kasutamisleping Nr. Tartu: Estonian Social Science Data Archive. Retrieved from
http://www.psych.ut.ee/esta/TARGET.EST/BAASINF/ESTA.YLD/POHIDOX/KASUTAMISLEPING.html
European Commission. (2012). Commission agrees way forward for modernising copyright in the digital economy. Brussels: European
Commission. Retrieved from http://europa.eu/rapid/press-release_MEMO-12-950_en.htm#PR_metaPressRelease_bottom
FORS. (n.d.). Order data. Lausanne: Swiss Centre of Expertise in the Social Sciences. Retrieved from
http://www2.unil.ch/daris/spip.php?rubrique62&lang=en
FSD. (n.d.). Agreement on Material Use Conditions. Tampere: Finnish Social Science Data Archive. Retrieved from Hyperlink
GESIS. (n.d.). Usage regulations - Dept. Data Archive for the Social Sciences. Cologne: GESIS Leibniz-Institute for Social Sciences. Retrieved
from http://www.gesis.org/en/services/data-analysis/data-archive-service/usage-regulations/
21. IPR bibliography
Gillmor, D. (2013). In Our Digital World You Don’t Own Stuff, You Just License it. The Guardian. Retrieved from
http://www.guardian.co.uk/commentisfree/2013/apr/05/digital-media-licensed-not-owned?
GSDB-EKKE. (n.d.). No Title. Athens: Greek Social Data Bank. Retrieved from
http://www.gsdb.gr/scripts/en/rel_files_en.pl?code=0&catal_code=148
Holmes, D. (2013). Copyright, explained. Retrieved from http://pandodaily.com/2013/02/01/pandohouse-rock-copyright-explained/
ISSDA. (n.d.). Contract. Dublin: Irish Social Science Data Archive. Retrieved from http://www.ucd.ie/t4cms/gui-contract.doc
JISC Digital Media. (n.d.). Copyright and Digital Images. JISC. Retrieved from http://www.jiscdigitalmedia.ac.uk/stillimages/advice/copyright-
and-digital-images/
LiDA. (n.d.). Terms of Use for Data. Kaunas: Lithuanian Data Archive for Social Sciences and Humanities. Retrieved from
http://www.lidata.eu/en/index.php?file=files/eng/data/terms_for_use_data.html
McGeever, M. (2006). IPR in Databases. Edinburgh. Retrieved from http://www.dcc.ac.uk/resources/briefing-papers/legal-watch-papers/ipr-
databases
McKiernan, E. C. (2012a). Who owns research data and the rights to publish? Retrieved from
http://emckiernan.wordpress.com/2012/10/24/who-owns-research-data-and-the-rights-to-publish-it/
McKiernan, E. C. (2012b). Who owns research data and the rights to publish? Part II. Retrieved from
http://emckiernan.wordpress.com/2012/10/31/who-owns-research-data-and-the-rights-to-publish-part-ii/
Nassiri, S., Worthington, B., & Tong, C. (2013). A comparison of standard licenses. Retrieved from http://research-data-
toolkit.herts.ac.uk/2013/04/comparison-of-open-licenses/
22. IPR bibliography
Oksanen, V., & Lindén, K. (2011). Open Content Licenses - How to choose the right one. In S. N. Moshagen & P. Langgård (Eds.), NEALT
Proceedings Series Vol. 13 (pp. 11–17). Riga.
doi:http://dspace.utlib.ee/dspace/bitstream/handle/10062/18959/Open_Content_Licenses.pdf?sequence=1
Reseau Quetelet. (n.d.). Free access for Research Purposes. Paris: French Data Archives for Social Sciences. Retrieved from
http://www.reseau-quetelet.cnrs.fr/spip/article.php3?id_article=154&lang=en
RODA. (n.d.). ACORD INDIVIDUAL DE ACCES aI UTILIZARE A DATELOR. Bucharest: Romanian Social Data Archive. Retrieved from
http://www.roda.ro/documente/Individual.pdf
SDA. (n.d.). Conditions of Data File Use. Prague: Czech Social Science Data Archive of the Institute of Sociology of the Academy of Sciences.
Retrieved from http://archiv.soc.cas.cz/registrace/en
SND. (n.d.). Conditions. Gothenburg: Swedish National Data Service. Retrieved from http://snd.gu.se/en/search-and-order-data/conditions
TARKI. (n.d.). User Declaration For Academical Purposes. Budapest: TÁRKI Social Research Institut. Retrieved from
http://www.tarki.hu/en/services/da/docs/user_declaration.pdf
Taylor, M. (2012a). Tutorial 19d: Open Access definitions and clarifications, part 4: licences. Sauropod Vertebra Picture of the Week
#AcademicSpring. Retrieved from http://svpow.com/2012/11/21/tutorial-19d-open-access-definitions-and-clarifications-part-4-licences/
Taylor, M. (2012b). Tutorial 19e: Open Access definitions and clarifications, part 5: Copyright. Sauropod Vertebra Picture of the Week
#AcademicSpring. Retrieved from http://svpow.com/2012/11/24/tutorial-19e-open-access-definitions-and-clarifications-part-5-copyright/
UK Data Archive. (n.d.). End User Licence. Colchester: UK Data Archive. Retrieved from
http://www.esds.ac.uk/aandp/access/licence.asp?print=1
WISDOM. (n.d.). Zugriffsklassen. Vienna: Vienna Institute for Social Science Documentation and Methodology. Retrieved from
http://www.wisdom.at/Datenarchiv/d_nutzungsbedingungen.aspx