Data repositories are much more than "black boxes" where data go in but may never come out. Rather, they are situated in communities, with contributors, users, reusers, and repository staff who may engage actively or passively with participants. This talk will explore the roles that Dataverse plays – or could play – in individual communities.
Metadata & Data Curation Services by Thu-Mai Christiandatascienceiqss
The Odum Institute was an early adopter of the Dataverse Network™ (DVN) virtual archive platform, transferring all of its holdings to the Virtual Data Center (VDC), the DVN’s precursor, in 2005. This presentation will illustrate the Odum Institute Data Archive’s integration of the Dataverse Network™ into its current data curation pipeline process and discuss the Dataverse Network’s role in the Institute’s tiered levels of data curation services.
Preservation of Research Data: Dataverse / Archivematica Integration by Allan...datascienceiqss
Scholars Portal, a program of the Ontario Council of University Libraries (OCUL), provides the technical infrastructure to store, preserve, and provide access to shared digital library collections in Ontario - including hosting a local instance of Dataverse since 2011. As part of a national project known as Portage (a project of the Canadian Association of Research Libraries), Scholars Portal is partnering with Artefactual Systems, Dataverse, the University of British Columbia, the University of Alberta, and others, to integrate Dataverse with preservation software Archivematica. When completed, this project will facilitate the long-term preservation of research data according to the Open Archival Information System (OAIS) Reference Model.
Data Publishing Models by Sünje Dallmeier-Tiessendatascienceiqss
Data Publishing is becoming an integral part of scholarly communication today. Thus, it is indispensable to understand how data publishing works across disciplines. Are there best practices others can learn from or even data publishing standards? How do they impact interoperability in the Open Science landscape? The presentation will look at a range of examples, and the main building blocks of data publishing today. The work has been conducted as part of the RDA Data Publishing Workflows group.
Dataverse in China: Internationalization, Curation and Promotion by Yin Shenqindatascienceiqss
Zhang Jilong & Yin Shenqin will discuss the internationalization development work done by Fudan University to support a Chinese language user interface in Dataverse. Additionally, the practice of data curation at Fudan University will be presented, as well as the branding and dissemination of Dataverse in China.
Data Citation Implementation Guidelines By Tim Clarkdatascienceiqss
This talk presents a set of detailed technical recommendations for operationalizing the Joint Declaration of Data Citation Principles (JDDCP) - the most widely agreed set of principle-based recommendations for direct scholarly data citation.
We will provide initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data.
We hope that these recommendations along with the new NISO JATS document schema revision, developed in parallel, will help accelerate the wide adoption of data citation in scholarly literature. We believe their adoption will enable open data transparency for validation, reuse and extension of scientific results; and will significantly counteract the problem of false positives in the literature.
Center for Open Science and the Open Science Framework: Dataverse Add-on by S...datascienceiqss
The Open Science Framework (OSF: http://osf.io; supported and maintained by the Center for Open Science - COS: http://centerforopenscience.org/) is a free, open source workflow management service and repository designed for scientists to manage and connect everything across their research process. One of the first add-on connections was Dataverse, which provides value to users through an easy connection as a repository service. This talk will introduce the Dataverse add-on connection and provide a technical view of how it was built and how it connects the OSF and Dataverse.
The Project TIER Dataverse: Archiving and Sharing Replicable Student Research...datascienceiqss
Richard Ball and Norm Medeiros will demonstrate how Dataverse is used within their Project TIER (Teaching Integrity in Empirical Economics) initiative to organize and showcase student work for transparency and reproducibility. Richard and Norm will discuss the prospect of extending Dataverse to serve as a resource for the Project TIER network of institutions and instructors.
February 18 2015 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Network Effects: RMap Project
Sheila M. Morrissey, Senior Researcher, ITHAKA
Metadata & Data Curation Services by Thu-Mai Christiandatascienceiqss
The Odum Institute was an early adopter of the Dataverse Network™ (DVN) virtual archive platform, transferring all of its holdings to the Virtual Data Center (VDC), the DVN’s precursor, in 2005. This presentation will illustrate the Odum Institute Data Archive’s integration of the Dataverse Network™ into its current data curation pipeline process and discuss the Dataverse Network’s role in the Institute’s tiered levels of data curation services.
Preservation of Research Data: Dataverse / Archivematica Integration by Allan...datascienceiqss
Scholars Portal, a program of the Ontario Council of University Libraries (OCUL), provides the technical infrastructure to store, preserve, and provide access to shared digital library collections in Ontario - including hosting a local instance of Dataverse since 2011. As part of a national project known as Portage (a project of the Canadian Association of Research Libraries), Scholars Portal is partnering with Artefactual Systems, Dataverse, the University of British Columbia, the University of Alberta, and others, to integrate Dataverse with preservation software Archivematica. When completed, this project will facilitate the long-term preservation of research data according to the Open Archival Information System (OAIS) Reference Model.
Data Publishing Models by Sünje Dallmeier-Tiessendatascienceiqss
Data Publishing is becoming an integral part of scholarly communication today. Thus, it is indispensable to understand how data publishing works across disciplines. Are there best practices others can learn from or even data publishing standards? How do they impact interoperability in the Open Science landscape? The presentation will look at a range of examples, and the main building blocks of data publishing today. The work has been conducted as part of the RDA Data Publishing Workflows group.
Dataverse in China: Internationalization, Curation and Promotion by Yin Shenqindatascienceiqss
Zhang Jilong & Yin Shenqin will discuss the internationalization development work done by Fudan University to support a Chinese language user interface in Dataverse. Additionally, the practice of data curation at Fudan University will be presented, as well as the branding and dissemination of Dataverse in China.
Data Citation Implementation Guidelines By Tim Clarkdatascienceiqss
This talk presents a set of detailed technical recommendations for operationalizing the Joint Declaration of Data Citation Principles (JDDCP) - the most widely agreed set of principle-based recommendations for direct scholarly data citation.
We will provide initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data.
We hope that these recommendations along with the new NISO JATS document schema revision, developed in parallel, will help accelerate the wide adoption of data citation in scholarly literature. We believe their adoption will enable open data transparency for validation, reuse and extension of scientific results; and will significantly counteract the problem of false positives in the literature.
Center for Open Science and the Open Science Framework: Dataverse Add-on by S...datascienceiqss
The Open Science Framework (OSF: http://osf.io; supported and maintained by the Center for Open Science - COS: http://centerforopenscience.org/) is a free, open source workflow management service and repository designed for scientists to manage and connect everything across their research process. One of the first add-on connections was Dataverse, which provides value to users through an easy connection as a repository service. This talk will introduce the Dataverse add-on connection and provide a technical view of how it was built and how it connects the OSF and Dataverse.
The Project TIER Dataverse: Archiving and Sharing Replicable Student Research...datascienceiqss
Richard Ball and Norm Medeiros will demonstrate how Dataverse is used within their Project TIER (Teaching Integrity in Empirical Economics) initiative to organize and showcase student work for transparency and reproducibility. Richard and Norm will discuss the prospect of extending Dataverse to serve as a resource for the Project TIER network of institutions and instructors.
February 18 2015 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Network Effects: RMap Project
Sheila M. Morrissey, Senior Researcher, ITHAKA
Persistent Identifier Services and their Metadata by John Kunzedatascienceiqss
Persistent identifiers (Pids) provide machine-actionable links to data and metadata that are vital to APIs (application programming interfaces) for publishing and citation. APIs are essentially request/response patterns that use Pids to reference things and metadata to describe not only the things themselves, but also any actions requested or taken. As a result, metadata design and standardization is wedded to API design and enhancement. With Pids as nouns and metadata as adjectives and qualifiers, Pid services play a key role in API implementation.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
Closing the scientific literature access gap with CORE - how to gain free acc...Nancy Pontika
Presented during the International Open Access Week 2020 for the Kerala Library Association, October 21, 2020.
The presentation is about CORE, a global harvester of open access scientific content and the CORE services on content discovery, managing content and access to raw data.
In order to be reused, research data must be discoverable.
The EPSRC Research Data Expectations* requires research organisations to maintain a data catalogue to record metadata about research data generated by EPSRC-funded research projects.
Universities are increasingly making research data assets available through repositories or other data portals.
The requirement for a UK research data discovery service has grown as universities become more involved in RDM and capacity develops.
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
In June 2013, the Alfred P. Sloan Foundation awarded NISO a grant to undertake a two-phase initiative to explore, identify, and advance standards and/or best practices related to a new suite of potential metrics in the community.The NISO Altmetrics Project has successfully moved to Phase Two, the formation of three working groups, A, B, & C. Working Group B, led by Kristi Holmes, PhD, Director, Galter Health Sciences Library at Northwestern University, and Mike Taylor, Senior Product Manager, Informetrics at Elsevier, is focused on the Output Types & Identifiers within the alternative metrics landscape.
NISO Webinar on data curation services at the CDLCarly Strasser
"Building communities and Services in Support of Data-Intensive Research". Webinar on 18 Sept 2013 for the NISO Webinar Series. This was part 2 of 2 for Data Curation
February 18 2014 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Capacity Building: Leveraging existing library networks to take on research data
Heidi Imker, Director of the Research Data Service, University of Illinois at Urbana-Champaign
Written and presented by Wolfgang Müller (HITS) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
Political Analysis Dataverse by Jonathan N. Katzdatascienceiqss
Jonathan Katz discussed the use of Dataverse as the central replication archive for all articled published in Political Analysis, the journal of the Society for Political Methodology, that he he co-edits. The journal requires all published articles to provide code and data to replicate their results in the journal’s data archive.
DataTags: Sharing Privacy Sensitive Data by Michael Bar-sinaidatascienceiqss
The DataTags framework makes it easy for data producers to deposit, data publishers to store and distribute, and data users to access and use datasets containing confidential information, in a standardized and responsible way. The talk will first introduce the concepts and tools behind DataTags, and then focus on the user-facing component of the system - Tagging Server (available today at datatags.org). We will conclude by describing how future versions of Dataverse will use DataTags to automatically handle sensitive datasets, that can only be shared under some restrictions.
Persistent Identifier Services and their Metadata by John Kunzedatascienceiqss
Persistent identifiers (Pids) provide machine-actionable links to data and metadata that are vital to APIs (application programming interfaces) for publishing and citation. APIs are essentially request/response patterns that use Pids to reference things and metadata to describe not only the things themselves, but also any actions requested or taken. As a result, metadata design and standardization is wedded to API design and enhancement. With Pids as nouns and metadata as adjectives and qualifiers, Pid services play a key role in API implementation.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
Closing the scientific literature access gap with CORE - how to gain free acc...Nancy Pontika
Presented during the International Open Access Week 2020 for the Kerala Library Association, October 21, 2020.
The presentation is about CORE, a global harvester of open access scientific content and the CORE services on content discovery, managing content and access to raw data.
In order to be reused, research data must be discoverable.
The EPSRC Research Data Expectations* requires research organisations to maintain a data catalogue to record metadata about research data generated by EPSRC-funded research projects.
Universities are increasingly making research data assets available through repositories or other data portals.
The requirement for a UK research data discovery service has grown as universities become more involved in RDM and capacity develops.
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
In June 2013, the Alfred P. Sloan Foundation awarded NISO a grant to undertake a two-phase initiative to explore, identify, and advance standards and/or best practices related to a new suite of potential metrics in the community.The NISO Altmetrics Project has successfully moved to Phase Two, the formation of three working groups, A, B, & C. Working Group B, led by Kristi Holmes, PhD, Director, Galter Health Sciences Library at Northwestern University, and Mike Taylor, Senior Product Manager, Informetrics at Elsevier, is focused on the Output Types & Identifiers within the alternative metrics landscape.
NISO Webinar on data curation services at the CDLCarly Strasser
"Building communities and Services in Support of Data-Intensive Research". Webinar on 18 Sept 2013 for the NISO Webinar Series. This was part 2 of 2 for Data Curation
February 18 2014 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Capacity Building: Leveraging existing library networks to take on research data
Heidi Imker, Director of the Research Data Service, University of Illinois at Urbana-Champaign
Written and presented by Wolfgang Müller (HITS) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
Political Analysis Dataverse by Jonathan N. Katzdatascienceiqss
Jonathan Katz discussed the use of Dataverse as the central replication archive for all articled published in Political Analysis, the journal of the Society for Political Methodology, that he he co-edits. The journal requires all published articles to provide code and data to replicate their results in the journal’s data archive.
DataTags: Sharing Privacy Sensitive Data by Michael Bar-sinaidatascienceiqss
The DataTags framework makes it easy for data producers to deposit, data publishers to store and distribute, and data users to access and use datasets containing confidential information, in a standardized and responsible way. The talk will first introduce the concepts and tools behind DataTags, and then focus on the user-facing component of the system - Tagging Server (available today at datatags.org). We will conclude by describing how future versions of Dataverse will use DataTags to automatically handle sensitive datasets, that can only be shared under some restrictions.
Sharing Data Through Plots with Plotly by Alex Johnsondatascienceiqss
Plotly is a web-based visualization and data analysis platform. Sharing Plotly plots in your dataverse creates a rich experience in which each user can interact with the data in whatever way best fits their needs: from zooming in and examining individual data points, to changing colors and styles, to importing the raw data into their favorite software environment for further analysis.
Geospatial Data Visualization: WorldMap Integration by Raman Prasaddatascienceiqss
The Boston Area Research Initiative (BARI) has started work to integrate the Dataverse and Harvard WorldMap systems. This will give Dataverse users the opportunity to map shapefiles as well as tabular files. The maps will be saved in the WorldMap system, allow users to take advantage of the WorldMap’s rich feature set as well as share the maps through Dataverse. This effort involved building APIs on both systems and connecting them via a small web application.
RedLink Network SSP 2015 (New and Noteworthy)Deepika Bajaj
RedLink Network is a community driven platform which aims to streamline information exchange across all channels of the Academic Publishing Industry. Academic Publishers, Institutions and Agencies will have the opportunity to move away from traditional and noisy sometimes emails and base the communication on a network that provides direct and easy access to information with regard to each other.
Email Marketing Tips, Tricks and Trends From Brands Winning In the Inbox (5/2...Emma Email Marketing
Want to learn the secrets and strategies of rockstar marketers like Tito’s Vodka, Dogfish Head, Mario Batali, and ReturnPath?
You'll learn easy-to-implement tips and strategies that you can put to work today, so you can drive excellent results for the rest of the year – and beyond!
RDA Fourth Plenary Keynote - Prof. Christine L. Borgman, Professor Presidential Chair in Information Studies at UCLA: "Data, Data, Everywhere, Nor Any Drop to Drink." Tuesday 23rd Sept 2014, Amsterdam, the Netherlands
https://rd-alliance.org/plenary-meetings/fourth-plenary/plenary4-programme.html
Jonathan Tedds Distinguished Lecture at DLab, UC Berkeley, 12 Sep 2013: "The ...Jonathan Tedds
http://dlab.berkeley.edu/event/open-research-challenge-peer-review-and-publication-research-data
A talk by Dr. Jonathan Tedds, Senior Research Fellow, D2K Data to Knowledge, Dept of Health Sciences, University of Leicester.
PI: #BRISSKit www.brisskit.le.ac.uk
PI: #PREPARDE www.le.ac.uk/projects/preparde
The Peer REview for Publication & Accreditation of Research data in the Earth sciences (PREPARDE) project seeks to capture the processes and procedures required to publish a scientific dataset, ranging from ingestion into a data repository, through to formal publication in a data journal. It will also address key issues arising in the data publication paradigm, namely, how does one peer-review a dataset, what criteria are needed for a repository to be considered objectively trustworthy, and how can datasets and journal publications be effectively cross-linked for the benefit of the wider research community.
I will discuss this and alternative approaches to research data management and publishing through examples in astronomy, biomedical and interdisciplinary research including the arts and humanities. Who can help in the long tail of research if lacking established data centers, archives or adequate institutional support? How much can we transfer from the so called “big data” sciences to other settings and where does the institution fit in with all this? What about software?
Publishing research data brings a wide and differing range of challenges for all involved, whatever the discipline. In PREPARDE we also considered the pre and post publication peer review paradigm, as implemented in the F1000 Research Publishing Model for the life sciences. Finally, in an era of truly international research how might we coordinate the many institutional, regional, national and international initiatives – has the time come for an international Research Data Alliance?
Slides from Monday 30 July - Data in the Scholarly Communications Life Cycle Course which is part of the FORCE11 Scholarly Communications Institute.
Presenter - Natasha Simons
2013 DataCite Summer Meeting - Closing Keynote: Building Community Engagement...datacite
2013 DataCite Summer Meeting - Making Research better
DataCite. Co-sponsored by CODATA.
Thursday, 19 September 2013 at 13:00 - Friday, 20 September 2013 at 12:30
Washington, DC. National Academy of Sciences
http://datacite.eventbrite.co.uk/
This presentation was provided by Andrew K. Pace of OCLC, during the 13th Annual NISO-BISG forum "Interoperability: From Silos to An Ecosystem," held on June 24, 2020.
Lesson 2 in a set of 10 created by DataONE on Best Practices fo Data Management. The full module can be downloaded from the DataONE.org website at: http://www.dataone.org/educaiton-modules. Released under a CC0 license, attribution and citation requested.
The fourth paradigm: data intensive scientific discovery - Jisc Digifest 2016Jisc
There is broad recognition within the scientific community that the emerging data deluge will fundamentally alter disciplines in areas throughout academic research. A wide variety of researchers - from scientists and engineers to social scientists and humanities researchers - will require tools, technologies, and platforms that seamlessly integrate into standard scientific methodologies and processes.
'The fourth paradigm' refers to the data management techniques and the computational systems needed to manipulate, visualize, and manage large amounts of research data. This talk will illustrate the challenges researchers will face, the opportunities these changes will afford, and the resulting implications for data-intensive researchers.
In addition, the talk will review the global movement towards open access, research repositories and open science and the importance of curation of digital data. The talk concludes with some comments on the research requirements for campus e-infrastructure and the end-to-end performance of the network.
State of the Art Informatics for Research Reproducibility, Reliability, and...Micah Altman
In March, I had the pleasure of being the inaugural speaker in a new lecture series (http://library.wustl.edu/research-data-testing/dss_speaker/dss_altman.html) initiated by the Libraries at the Washington University in St. Louis Libraries -- dedicated to the topics of data reproducibility, citation, sharing, privacy, and management.
In the presentation embedded below, I provide an overview of the major categories of new initiatives to promote research reproducibility, reliability, and reuse and related state of the art in informatics methods for managing data.
"Open Science, Open Data" training for participants of Software Writing Skills for Your Research - Workshop for Proficient, Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences, Telegrafenberg, December 16, 2015
Research Data Management in GLAM: Managing Data for Cultural HeritageSarah Anna Stewart
Presentation given at the 'Open Science Infrastructures for Big Cultural Data' - Advanced International Masterclass in Plovdiv, Bulgaria. Dec. 13-15, 2018
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Doing research better: The role of meta‐dataGarethKnight
Presentation given by David Leon, Professor of Epidemiology at the London School of Hygiene and Tropical Medicine in January 2012. Subsequently reused at various internal events
Similar to Dataverse in the Universe of Data by Christine L. Borgman (20)
Big Data Repository for Structural Biology: Challenges and Opportunities by P...datascienceiqss
SBGrid (Morin et al., 2013, eLIFE and www.sbgrid.org) is a Harvard based structural biology global computing consortium with a primary focus on the curation of research software. Dr. Sliz will discuss a recent SBGrid project that aims to establish a repository for experimental datasets from SBGrid laboratories. Issues of handling large data volumes, data validation and repository sustainability will be addressed in this talk.
DataTags: Sharing Privacy Sensitive Data by Latanya Sweeneydatascienceiqss
The DataTags framework makes it easy for data producers to deposit, data publishers to store and distribute, and data users to access and use datasets containing confidential information, in a standardized and responsible way. The talk will first introduce the concepts and tools behind DataTags, and then focus on the user-facing component of the system - Tagging Server (available today at datatags.org). We will conclude by describing how future versions of Dataverse will use DataTags to automatically handle sensitive datasets, that can only be shared under some restrictions.
Data Analysis in Dataverse & Visualization of Datasets on Historical Maps by ...datascienceiqss
The CLIO INFRA project (http://www.clio-infra.eu) hosted at the International Institute of Social History (IISH, http://www.socialhistory.org) integrates a number of data(hubs) on global social, economic and institutional indicators over the past five centuries. Considering a switch to Dataverse, the IISH is currently developing visualization tools that fit on top of Dataverse, especially historical maps with temporally accurate borders, such as provided in the NLGIS (http://nlgis.nl), Labour conflicts (http://laborconflicts.socialhistory.org) projects.
This talk will introduce the Dataverse widget developed to extract, transform and load data from datasets storage to platform independent internal data warehouses with possibilities to validate and check the quality of research datasets.
Data in Brief and Dataverse: Incentivizing Authors to Share Data by Paige Sha...datascienceiqss
Data in Brief, an Open Access journal published by Elsevier, exclusively publishes data articles wherein researchers describe their datasets. Data in Brief requires that all data be made publicly available either directly with the article as supplementary files or in a public repository. Data in Brief has teamed up with Dataverse to provide a venue for authors to archive and openly share their data.
Data FAIRport Skunkworks: Common Repository Access Via Meta-Metadata Descript...datascienceiqss
It would be useful to be able to discover what kinds of data are contained in the myriad general-purpose public data repositories. It would be even better if it were possible to query that data and/or have that data conform to a particular context-dependent data format. This was the ambition of the Data FAIRport project. I will be demonstrating the "strawman" demonstration of a fully-functional Data FAIRport, where the meta/data in a public repository can be "projected" into one of a number of different context-dependent formats, such that it can be cross-queried in combination with the (potentially "projected") data from other repositories.
Towards a common deposit api (the dataverse example) Elizabeth Quigley + Phil...datascienceiqss
For the past few years Dataverse has been using the SWORD protocol as the standard for a Data Deposit API, but is this the standard all repositories should use for Data Deposit APIs? We will discuss the good parts and the challenges of this approach. Additionally this presentation will lead into the Panel Discussion consisting of various stakeholders from publishers, domain and general repositories, funding agencies, researchers, and industry.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Overview on Edible Vaccine: Pros & Cons with Mechanism
Dataverse in the Universe of Data by Christine L. Borgman
1. Dataverse in the Universe of Data
Dataverse Community Meeting
Harvard University
June 10, 2015
Christine L. Borgman
Professor and Presidential Chair in Information Studies
University of California, Los Angeles
PhD, Stanford University, Dept of Communication
@scitechprof
3. Theme issue ‘Celebrating 350 years of
Philosophical Transactions: life sciences
papers’ compiled and edited by Linda
Partridge
19 April 2015; volume 370, issue 1666
4. Publications <–> Data
Publications are
arguments made
by authors, and
data are the
evidence used to
support the
arguments.
C.L. Borgman (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press
5. • Australian Research Council
– Code for the Responsible Conduct of Research
– Data management plans
• National Science Foundation
– Data sharing requirements
– Data management plans
• U.S. Federal policy
– Open access to publications
– Open access to data
• European Union
– European Open Data Challenge
– OpenAIRE
• Research Councils of the UK
– Open access publishing
– Provisions for access to data
5
Open access policies
6. Big Data, Little Data, No Data:
Scholarship in the Networked World
• Part I: Data and Scholarship
– Ch 1: Provocations
– Ch 2: What Are Data?
– Ch 3: Data Scholarship
– Ch 4: Data Diversity
• Part II: Case Studies in Data Scholarship
– Ch 5: Data Scholarship in the Sciences
– Ch 6: Data Scholarship in the Social Sciences
– Ch 7: Data Scholarship in the Humanities
• Part III: Data Policy and Practice
– Ch 8: Releasing, Sharing, and Reusing Data
– Ch 9: Credit, Attribution, and Discovery
– Ch 10: What to Keep and Why
6
7. Data, Sharing, Release, and Reuse
• Defining data
• Making useful data
• Making data useful
• Keeping data useful
7
Persistent URL: photography.si.edu/SearchImage.aspx?id=5799
Repository: Smithsonian Institution Archives
10. Long tail of data
Volumeofdata
Number of researchers
Slide: The Institute for Empowering Long Tail Research
10
11. Open Data: Free
• A piece of data or
content is open if anyone
is free to use, reuse, and
redistribute it — subject
only, at most, to the
requirement to attribute
and/or share-alike
11
Open Data Commons. (2013).
State Library and Archives of
Florida, 1922. Flickr commons
photo
12.
13. Open Data: Useful
• Openness, flexibility, transparency,
legal conformity, protection of
intellectual property, formal
responsibility, professionalism,
interoperability, quality, security,
efficiency, accountability, and
sustainability.
13
Organization for Economic Cooperation and Development. (2007).
OECD Principles and Guidelines for Access to Research Data from Public Funding.
http://www.oecd.org/dataoecd/9/61/38500813.pdf
15. 15
Data are representations of
observations, objects, or other entities
used as evidence of phenomena for
the purposes of research or
scholarship.
C.L. Borgman (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press
hudsonalpha.org
17. Research process
• Models and theories
• Research questions
• Methods
– Tools
– Data sources
– Practices
– Infrastructure
– Domain expertise
17
18. Research process
• Models and theories
• Research questions
• Methods
– Tools
– Data sources
– Practices
– Infrastructure
– Domain expertise
18Commons photo: Science Gossip, 1894
19. 19
Pepe, A., Mayernik, M. S., Borgman, C. L. & Van de Sompel, H. (2010). From Artifacts to Aggregations: Modeling Scientific
Life Cycles on the Semantic Web. Journal of the American Society for Information Science and Technology, 61(3): 567–582.
21. Big Science <–> Little Science
• Large instruments
• High cost
• Long duration
• Many collaborators
• Distributed work
• Domain expertise
• Small instruments
• Low cost
• Short duration
• Small teams
• Local work
• Domain expertise
21
Sloan Digital Sky Survey
Sensor networks for science
24. Center for Embedded Networked Sensing
24
• NSF Science & Tech Ctr, 2002-2012
• 5 universities, plus partners
• 300 members
• Computer science and engineering
• Science application areas
Slide by Jason Fisher, UC-Merced,
Center for Embedded Networked Sensing (CENS)
25. Science <–> Data
Engineering researcher:
“Temperature is temperature.”
Biologist: “There are hundreds
of ways to measure
temperature. ‘The temperature is
98’ is low-value compared to, ‘the
temperature of the surface,
measured by the infrared thermopile,
model number XYZ, is 98.’ That
means it is measuring a proxy for a
temperature, rather than being in
contact with a probe, and it is
measuring from a distance. The
accuracy is plus or minus .05 of a
degree. I [also] want to know that it
was taken outside versus inside a
controlled environment, how long it
had been in place, and the last time
it was calibrated, which might tell me
whether it has drifted.."CENS Robotics team
29. Making data useful
29
Page 105 of "The Street railway
journal" (1884); Flickr Commons
July 19, 1922. State Library and Archives
of Florida. Flickr commons photo
32. Some ways to release data
• Centralized data production
– Top down investments in data
– Common data archive
• Decentralized data production
– Bottom up investments in data
– Pool domain resources later
• Domain-independent aggregators
– University repositories
– Figshare, Slideshare, Dataverse…
• Post on lab / personal websites
• Share privately upon request
32
35. Lack of incentives to share data
• Labor to document data
• Benefits to unknown others
• Competition
• Control
• Confidentiality…
35
Image source: www.buildingsrus.co.uk/.../ target1.htm
36. Everyone is overwhelmed with life and
email and, in academia, trying to get
funding and write papers. Whether
something is open or not open is not
highest on the priority list. There’s still
need for making people aware of open
science issues and making it easy for
them to participate if they want to.
Jonathan Eisen, genetics professor at the
University of California, Davis
DESPITE BEING GOOD FOR YOU AND FOR SCIENCE,
TOO MANY CHALLENGES AND TOO LITTLE TIME
Rewards for
publications
Effort to
document
data
Competition,
priority
Control,
ownership
Slide courtesy of Merce Crosas, Harvard IQSS 36
37. Survey with 1700 respondents from Science (2011) peer reviewers
Access data from published work
Ask colleagues for data Archival location
Size of data
Slide courtesy of Merce Crosas, Harvard IQSS 37
38. Lack of incentives to reuse data
• Identify useful data
– Documentation
– Interpretation
– Software
• Cleaning
• Trust
• Credit
• Licensing…
http://fyi.uiowa.edu/wp-content/uploads/2011/10/utopia_in_four_movements_filmstill5_utopiasign.jpg
38
40. Describing and attributing data
• Compound objects
– Observations
– Software
– Protocols…
• Attribution
– Investigators
– Data collectors
– Analysts…
• Ownership, responsibility
Mary Jane Rathbun (1860-1943), working with crab specimens
41. Metadata
• Metadata is structured
information that describes,
explains, locates, or
otherwise makes it easier
to retrieve, use, or manage
an information resource.
– descriptive
– structural
– administrative
National Information Standards Organization 2004 photo by @kissane
42. Provenance
• Libraries: Origin or source
• Museums: Chain of custody
• Internet: Provenance is information about
entities, activities, and people involved in
producing a piece of data or thing, which can
be used to form assessments about its quality,
reliability or trustworthiness. (World Wide Web
Consortium (W3C) Provenance working group)
British Library, provenance record:
Bestiary - caption: 'Owl mobbed by
smaller birds'
43. Keeping Data Useful
Flickr Commons Photo: Women working in the Pinion Department at Bulova Watch,
Southern Methodist University Libraries; Creator: Richie, Robert Yarnall (1908-1984), 1937
51. Conclusions
• Defining data
– Representations used as evidence
– One person’s signal is another’s noise
• Making useful data
– Models, questions, methods
– Domain expertise
– Data science expertise
• Making data useful
– Documentation, description, identity, linking
– Incentives for release and reuse
– Curation and stewardship expertise
• Keeping data useful
– Infrastructure investments
– Workforce development
– Trust fabric
51
52. Acknowledgements
UCLA Data Practices team
• Peter Darch, Milena Golshan, Irene
Pasquetto, Ashley Sands, Sharon
Traweek, Camille Mathieu
• Former members: Rebekah
Cummings, David Fearon, Ariel
Hernandez, Elaine Levia, Jaklyn
Nunga, Rachel Mandel, Matthew
Mayernik, Alberto Pepe, Kalpana
Shankar, Katie Shilton, Jillian
Wallis, Laura Wynholds, Kan
Zhang
• Research funding: National
Science Foundation, Alfred P.
Sloan Foundation, Microsoft
Research, DANS-
Netherlands
• University of Oxford: Balliol
College, Oliver Smithies
Fellowship, Oxford Internet
Institute, Oxford eResearch
Center, Bodleian Library