The Infrastructure for Alternative Metrics: What do we need to compare digital apples to digital apples?
Todd Carpenter, Executive Director, NISO
Presented at AAAS Annual Meeting: February 16, 2014
Chicago, IL
Todd Carpenter's talk at Elsevier Booth During ALA Annual Conference in Las Vegas about NISO alternative assessment project and the results of the first phase of the project
Todd Carpenter's Presentation during the Library Assessment Conference 2014 in Seattle, WA on August 2014 at University of Washington. During this presentation, Todd covered the output of Phase One of NISO's alternative metrics assessment initiative.
Todd Carpenter from the National Information Standards Organization (NISO) discussed the need for standards for alternative metrics to evaluate scholarly output beyond citations. NISO is launching an Alternative Assessment Initiative in two phases to define key terms, compare data across providers, ensure consistency in measurements, and address issues like author disambiguation and data sharing to help establish trust in alternative metrics. The goal is to publish final recommendations by June 2016 after gathering input from working groups and a trial use period. However, some critics argue it is too soon for standards or that NISO may not be able to take on this challenging task.
Reputation Management for Early Career ResearchersMicah Altman
In the rapidly changing world of research and scholarly communications, researchers are faced with a fast growing range of options to publicly disseminate, review, and discuss research—options which will affect their long-term reputation. Early career scholars must be especially thoughtful in choosing how much effort to invest in dissemination and communication, and what strategies to use.
Dr. Micah Altman briefly reviews a number of bibliometric and scientometric studies of quantitative research impact, a sampling of influential qualitative writings advising this area, and an environmental scan of emerging researcher profile systems. Based on this review, and on professional experience on dozens of review panels, Dr. Altman suggests some steps early career researchers may consider when disseminating their research and participating in public reviews and discussion.
The NISO Altmetrics Initiative aims to develop standards around altmetrics through a consensus-based process. [NISO] is coordinating a two-phase project to define key issues in altmetrics and establish working groups. They held initial community meetings to identify priorities such as ensuring consistent measurement, valid data, and addressing issues like gaming. The goal is recommended best practices and standards to support assessment practices and infrastructure for new forms of scholarly communication.
1) The document discusses the origins and early ambitions of altmetrics from 2010, including crowdsourcing peer review and measuring broader impact.
2) It analyzes the current state of altmetrics, including measuring the impact of alternative outputs like research data and software. It also examines measuring broader social reach and qualitative case studies of narrative impact.
3) The document predicts future challenges for altmetrics, including developing more complex methodologies and theoretical frameworks and greater integration with research assessment ecosystems. It notes ongoing issues around data ownership and the shifting meaning of "altmetrics" over time.
This document provides an overview of qualitative data analysis software (QDAS) and the web-based software webQDA. It discusses the benefits of using QDAS to organize and analyze qualitative data. The document outlines the history of major QDAS programs and describes some of the key features and capabilities of webQDA, including its ability to code and categorize data from various sources to facilitate analysis and answer research questions. WebQDA allows for collaborative qualitative analysis in an online environment.
Todd Carpenter's talk at Elsevier Booth During ALA Annual Conference in Las Vegas about NISO alternative assessment project and the results of the first phase of the project
Todd Carpenter's Presentation during the Library Assessment Conference 2014 in Seattle, WA on August 2014 at University of Washington. During this presentation, Todd covered the output of Phase One of NISO's alternative metrics assessment initiative.
Todd Carpenter from the National Information Standards Organization (NISO) discussed the need for standards for alternative metrics to evaluate scholarly output beyond citations. NISO is launching an Alternative Assessment Initiative in two phases to define key terms, compare data across providers, ensure consistency in measurements, and address issues like author disambiguation and data sharing to help establish trust in alternative metrics. The goal is to publish final recommendations by June 2016 after gathering input from working groups and a trial use period. However, some critics argue it is too soon for standards or that NISO may not be able to take on this challenging task.
Reputation Management for Early Career ResearchersMicah Altman
In the rapidly changing world of research and scholarly communications, researchers are faced with a fast growing range of options to publicly disseminate, review, and discuss research—options which will affect their long-term reputation. Early career scholars must be especially thoughtful in choosing how much effort to invest in dissemination and communication, and what strategies to use.
Dr. Micah Altman briefly reviews a number of bibliometric and scientometric studies of quantitative research impact, a sampling of influential qualitative writings advising this area, and an environmental scan of emerging researcher profile systems. Based on this review, and on professional experience on dozens of review panels, Dr. Altman suggests some steps early career researchers may consider when disseminating their research and participating in public reviews and discussion.
The NISO Altmetrics Initiative aims to develop standards around altmetrics through a consensus-based process. [NISO] is coordinating a two-phase project to define key issues in altmetrics and establish working groups. They held initial community meetings to identify priorities such as ensuring consistent measurement, valid data, and addressing issues like gaming. The goal is recommended best practices and standards to support assessment practices and infrastructure for new forms of scholarly communication.
1) The document discusses the origins and early ambitions of altmetrics from 2010, including crowdsourcing peer review and measuring broader impact.
2) It analyzes the current state of altmetrics, including measuring the impact of alternative outputs like research data and software. It also examines measuring broader social reach and qualitative case studies of narrative impact.
3) The document predicts future challenges for altmetrics, including developing more complex methodologies and theoretical frameworks and greater integration with research assessment ecosystems. It notes ongoing issues around data ownership and the shifting meaning of "altmetrics" over time.
This document provides an overview of qualitative data analysis software (QDAS) and the web-based software webQDA. It discusses the benefits of using QDAS to organize and analyze qualitative data. The document outlines the history of major QDAS programs and describes some of the key features and capabilities of webQDA, including its ability to code and categorize data from various sources to facilitate analysis and answer research questions. WebQDA allows for collaborative qualitative analysis in an online environment.
Assessing Digital Output in New Ways
Mike Taylor, Research Specialist, Elsevier Labs
Presented during NISO/BISG 8th Annual Changing Standards Landscape on June 27, 2014
The slides from the Machine Learning Summers School 2015 in Sydney on Machine Learning for Recommender Systems. Collaborative filtering algorithms, Context-aware methods, Restricted Boltzmann Machines, Recurrent Neural Networks, Tensor Factorization, etc.
Many people are surprised to learn that, even though they don’t participate on social media and only use their computers for work, they have a digital life. This is partly because publicly-available information about you is collected from the internet, and this information is used by companies to create records about you. Join Kimberley Barker for an overview of topics such as digital privacy, online reputation management, personal branding, and online identity.
Search, Serendipity and the Researcher ExperienceLettie Conrad
When considering academic researchers’ information-seeking and retrieval needs, we often focus on search – optimizing for search, Google-like search for libraries, user preferences for one-box quick-search tools, and so on. But what about unplanned instances of discovery? Are new technologies, such as text mining and natural language processing, enabling new pathways that lead researchers to relevant material, perhaps even leading to surprising new connections across disciplines? Conversely, with the prevalence of satisficing, does serendipity even play a role when searching for information about a scholarly topic?_x000D_
Through a study of undergraduate students and their faculty members, as well as a survey of publisher and website offerings, this talk will summarize common user pathways and how today’s students and faculty use content recommendation tools with recommendations for how libraries and the scholarly communications community might respond.
July IAP: Confidential Information - Storage, Sharing, & Publication - with M...Micah Altman
This class focuses on the tools and good practices for storing confidential data, sharing data for collaboration, and publishing data or derivative results for broad use. Topics covered in this class include: an overview of information security standards and frameworks; information security core practices (credentials, authentication, authorization, and auditing); information partitioning and secure linking; file, disk, and network encryption tools and practices; cloud storage practices for confidential information; data “de-identification” tools and practices; statistical disclosure limitation approaches and tools; and data use agreements.
Systematic study of data is called data science. Data science is a multi-disciplinary field which uses scientific methods, processes, algorithms and systems to extract the hidden knowledge from data. This knowledge helps in decision making.
Among various programming languages available, Python is best suited for data science and is most popular among the data scientists as it provides wide range of libraries such as to accomplish the desired tasks.1. Data exploration and analysis : Pandas; NumPy; SciPy;
2. Data visualization: Matplotlib; Seaborn; Datashader;
3. Classical machine learning: Scikit-Learn, StatsModels
4. Deep learning: Keras, TensorFlow
5. Data storage and big data frameworks: Apache Spark; Apache Hadoop; HDFS etc. In this PPT we will be learning about introduction to data science and Python, their applications and use cases.
But Were We Successful: Using Online Asynchronous Focus Groups to Evaluate Li...Andrea Payant
USU launched a program in 2016 to connect researchers seeking federal funding with librarians to assist them with data management. This program assisted over 100 researchers, but was it successful? Our presentation will discuss how we evaluated the success of this program using online asynchronous focus groups (OAFG) in conjunction with a traditional survey. Our cross-institutional research team will share our findings as well as the challenges and successes of using OAFGs to assess library services.
NOVA Data Science Meetup 1/19/2017 - Presentation 1NOVA DATASCIENCE
The document discusses cognitive computing and its applications. It begins with an agenda that includes an overview of cognitive computing and examples of its use. It then discusses IBM Research's work leading to the development of Watson. Key points made include that most data is now unstructured, cognitive systems can reason, learn and understand like humans, and examples of cognitive computing applications in various domains.
Open Data Bay Area: Interesting Problems in Academic DataWilliam Gunn
This document discusses several problems in academic data including:
1. Academic data includes metadata about scholarly outputs but is not like commercial data from companies.
2. Academia has a conservative culture and incentives prioritize publishing over openly sharing data and code.
3. Issues around making data and code citable and improving reproducibility need to be addressed through initiatives like DateCite and CrossRef.
4. Problems like author disambiguation, increasing age of grant awardees, and recommender systems would benefit from better academic data.
The document discusses the Vienna Data Science Group (VDSG), a nonprofit organization that aims to promote data science. It has diverse members from various academic and professional fields. VDSG brings data science to life through talks, conferences, workshops, and networking events. It also discusses the impact of data science on society through applications like autonomous vehicles, smart home devices, and predictive analytics. Data science is changing areas like mobility, sports, finance, and advertising. Emerging technologies like the Internet of Things and predictive modeling raise important questions for society regarding privacy, ethics, and the limits of data-driven decisions.
All Edge: Understanding the New Workplace NetworksClay Spinuzzi
I presented this talk to the Austin Chamber of Commerce in November 2013. How are new information and communication technologies enabling us to work together in new ways? I discuss some of the lessons from case studies I've conducted in Austin.
Speakers: Laurie Kaplan, ProQuest; Nettie Lagace, NISO. This program provides an update on several NISO projects potentially of interest to serials librarians, including PIE-J (Presentation and Identification of E-Journals), ODI (Open Discovery Initiative), KBART (KnowledgeBases and Related Tools), and OAMI (Open Access Metadata and Indicators). The projects are at different stages in their creation, publication and revision lifecycles, but all require community understanding and input. Participants will receive practical information on how the initiatives affect their daily work and how their experiences can shape the creation and uptake of consensus-based community standards in the library and information industry.
- NISO is a non-profit trade association that develops standards related to publishing. It has over 150 members and focuses on areas like metadata, identifiers, and discovery.
- NISO is currently working on standards around presenting e-journals, open discovery of content, demand-driven acquisition of books, and open access metadata indicators.
- The e-journal standard provides guidelines for title display, ISSN use, and citations. Open discovery aims to help libraries assess content participation in discovery services. Demand-driven acquisition is developing a flexible model for libraries. Open access metadata focuses on clear readership rights indicators.
This document discusses the future of library resource discovery and how it can create new experiences for users and librarians. It was presented at the ER&L conference in Austin, Texas on February 23, 2015 by Nettie Lagace and Marshall Breeding. The document focuses on improving search and discovery of library resources.
This document summarizes the objectives and activities of a working group on rights metadata. The working group aims to:
1. Develop a format for bibliographic metadata that describes the readership rights of scholarly works.
2. Recommend mechanisms for publishing and distributing this rights metadata.
3. Report on the feasibility of including re-use rights information and incorporating it into the outputs.
4. Report on how adopting these outputs would address specific use cases developed by the working group.
The working group is co-chaired by representatives from PLoS, CrossRef, and SPARC. It includes members from various organizations. The group discussed tags for indicating whether a work is freely available to read
NISO's Altmetrics Initiative, a presentation by Nettie Lagace for ICIS: Innovating Communication in Scholarship meeting at UC Davis February 13-14, 2014
How ONIX-PL Can Help License Data Flow
Todd Carpenter, NISO; Selden Durgom Lamoureux, SDLinforms; and Ashley Bass, ProQuest
Presented at Charleston Conference 2013
Uncork Your Licenses!How ONIX-PL can help License data flow tour of the ONIX-PL License Encoding Project…
Selden Durgom Lamoureux
SDLinforms
Charleston Conference
November 8, 2013
Assessing Digital Output in New Ways
Mike Taylor, Research Specialist, Elsevier Labs
Presented during NISO/BISG 8th Annual Changing Standards Landscape on June 27, 2014
The slides from the Machine Learning Summers School 2015 in Sydney on Machine Learning for Recommender Systems. Collaborative filtering algorithms, Context-aware methods, Restricted Boltzmann Machines, Recurrent Neural Networks, Tensor Factorization, etc.
Many people are surprised to learn that, even though they don’t participate on social media and only use their computers for work, they have a digital life. This is partly because publicly-available information about you is collected from the internet, and this information is used by companies to create records about you. Join Kimberley Barker for an overview of topics such as digital privacy, online reputation management, personal branding, and online identity.
Search, Serendipity and the Researcher ExperienceLettie Conrad
When considering academic researchers’ information-seeking and retrieval needs, we often focus on search – optimizing for search, Google-like search for libraries, user preferences for one-box quick-search tools, and so on. But what about unplanned instances of discovery? Are new technologies, such as text mining and natural language processing, enabling new pathways that lead researchers to relevant material, perhaps even leading to surprising new connections across disciplines? Conversely, with the prevalence of satisficing, does serendipity even play a role when searching for information about a scholarly topic?_x000D_
Through a study of undergraduate students and their faculty members, as well as a survey of publisher and website offerings, this talk will summarize common user pathways and how today’s students and faculty use content recommendation tools with recommendations for how libraries and the scholarly communications community might respond.
July IAP: Confidential Information - Storage, Sharing, & Publication - with M...Micah Altman
This class focuses on the tools and good practices for storing confidential data, sharing data for collaboration, and publishing data or derivative results for broad use. Topics covered in this class include: an overview of information security standards and frameworks; information security core practices (credentials, authentication, authorization, and auditing); information partitioning and secure linking; file, disk, and network encryption tools and practices; cloud storage practices for confidential information; data “de-identification” tools and practices; statistical disclosure limitation approaches and tools; and data use agreements.
Systematic study of data is called data science. Data science is a multi-disciplinary field which uses scientific methods, processes, algorithms and systems to extract the hidden knowledge from data. This knowledge helps in decision making.
Among various programming languages available, Python is best suited for data science and is most popular among the data scientists as it provides wide range of libraries such as to accomplish the desired tasks.1. Data exploration and analysis : Pandas; NumPy; SciPy;
2. Data visualization: Matplotlib; Seaborn; Datashader;
3. Classical machine learning: Scikit-Learn, StatsModels
4. Deep learning: Keras, TensorFlow
5. Data storage and big data frameworks: Apache Spark; Apache Hadoop; HDFS etc. In this PPT we will be learning about introduction to data science and Python, their applications and use cases.
But Were We Successful: Using Online Asynchronous Focus Groups to Evaluate Li...Andrea Payant
USU launched a program in 2016 to connect researchers seeking federal funding with librarians to assist them with data management. This program assisted over 100 researchers, but was it successful? Our presentation will discuss how we evaluated the success of this program using online asynchronous focus groups (OAFG) in conjunction with a traditional survey. Our cross-institutional research team will share our findings as well as the challenges and successes of using OAFGs to assess library services.
NOVA Data Science Meetup 1/19/2017 - Presentation 1NOVA DATASCIENCE
The document discusses cognitive computing and its applications. It begins with an agenda that includes an overview of cognitive computing and examples of its use. It then discusses IBM Research's work leading to the development of Watson. Key points made include that most data is now unstructured, cognitive systems can reason, learn and understand like humans, and examples of cognitive computing applications in various domains.
Open Data Bay Area: Interesting Problems in Academic DataWilliam Gunn
This document discusses several problems in academic data including:
1. Academic data includes metadata about scholarly outputs but is not like commercial data from companies.
2. Academia has a conservative culture and incentives prioritize publishing over openly sharing data and code.
3. Issues around making data and code citable and improving reproducibility need to be addressed through initiatives like DateCite and CrossRef.
4. Problems like author disambiguation, increasing age of grant awardees, and recommender systems would benefit from better academic data.
The document discusses the Vienna Data Science Group (VDSG), a nonprofit organization that aims to promote data science. It has diverse members from various academic and professional fields. VDSG brings data science to life through talks, conferences, workshops, and networking events. It also discusses the impact of data science on society through applications like autonomous vehicles, smart home devices, and predictive analytics. Data science is changing areas like mobility, sports, finance, and advertising. Emerging technologies like the Internet of Things and predictive modeling raise important questions for society regarding privacy, ethics, and the limits of data-driven decisions.
All Edge: Understanding the New Workplace NetworksClay Spinuzzi
I presented this talk to the Austin Chamber of Commerce in November 2013. How are new information and communication technologies enabling us to work together in new ways? I discuss some of the lessons from case studies I've conducted in Austin.
Speakers: Laurie Kaplan, ProQuest; Nettie Lagace, NISO. This program provides an update on several NISO projects potentially of interest to serials librarians, including PIE-J (Presentation and Identification of E-Journals), ODI (Open Discovery Initiative), KBART (KnowledgeBases and Related Tools), and OAMI (Open Access Metadata and Indicators). The projects are at different stages in their creation, publication and revision lifecycles, but all require community understanding and input. Participants will receive practical information on how the initiatives affect their daily work and how their experiences can shape the creation and uptake of consensus-based community standards in the library and information industry.
- NISO is a non-profit trade association that develops standards related to publishing. It has over 150 members and focuses on areas like metadata, identifiers, and discovery.
- NISO is currently working on standards around presenting e-journals, open discovery of content, demand-driven acquisition of books, and open access metadata indicators.
- The e-journal standard provides guidelines for title display, ISSN use, and citations. Open discovery aims to help libraries assess content participation in discovery services. Demand-driven acquisition is developing a flexible model for libraries. Open access metadata focuses on clear readership rights indicators.
This document discusses the future of library resource discovery and how it can create new experiences for users and librarians. It was presented at the ER&L conference in Austin, Texas on February 23, 2015 by Nettie Lagace and Marshall Breeding. The document focuses on improving search and discovery of library resources.
This document summarizes the objectives and activities of a working group on rights metadata. The working group aims to:
1. Develop a format for bibliographic metadata that describes the readership rights of scholarly works.
2. Recommend mechanisms for publishing and distributing this rights metadata.
3. Report on the feasibility of including re-use rights information and incorporating it into the outputs.
4. Report on how adopting these outputs would address specific use cases developed by the working group.
The working group is co-chaired by representatives from PLoS, CrossRef, and SPARC. It includes members from various organizations. The group discussed tags for indicating whether a work is freely available to read
NISO's Altmetrics Initiative, a presentation by Nettie Lagace for ICIS: Innovating Communication in Scholarship meeting at UC Davis February 13-14, 2014
How ONIX-PL Can Help License Data Flow
Todd Carpenter, NISO; Selden Durgom Lamoureux, SDLinforms; and Ashley Bass, ProQuest
Presented at Charleston Conference 2013
Uncork Your Licenses!How ONIX-PL can help License data flow tour of the ONIX-PL License Encoding Project…
Selden Durgom Lamoureux
SDLinforms
Charleston Conference
November 8, 2013
This document provides instructions for an engineering project where student teams must design and build two paper airplanes - one to fly as far as possible and one to stay in the air as long. The document outlines requirements, materials, forces that impact flight, design considerations for each plane type, and potential modifications to improve flight performance. The goal is for students to work as a team, apply engineering concepts, and design paper airplanes to optimize for distance or time in the air.
Presentation at the H2020-CEF Infoday, 16 January 2014 http://ec.europa.eu/digital-agenda/en/news/information-and-networking-days-h2020-work-programme-2014-2015-connecting-europe-facility
Interlinking Multimedia: How to Apply Linked Data Principles to Multimedia F...Raphael Troncy
The document discusses applying linked data principles to identify and describe fragments of multimedia content like images, videos, and audio. It proposes using URIs to uniquely identify multimedia fragments and deploying multimedia metadata in the semantic web. The W3C Media Fragments Working Group aims to provide mechanisms for identifying multimedia fragments on the web. Examples show retrieving video fragments by URI and representing them semantically in RDF. Open issues include content negotiation between media and semantic representations of fragments.
Challenges for the Language Technology IndustryAntoine Isaac
This document summarizes challenges for the language technology industry in Europe related to Europeana, a platform providing access to cultural heritage collections across Europe. It notes that Europeana provides access to over 33 million objects from over 2,300 contributors in 36 countries, with metadata in 33 languages. However, it faces challenges in facilitating re-use and access across languages due to the diversity of languages and domains in its collections. It discusses the need for automatic translation and natural language processing tools to address multilingual search and access issues at Europeana's scale. The document also outlines resource constraints for libraries, archives, and museums in developing language technologies, and their role in providing open data and use cases to the industry.
The document discusses finding and organizing media like photos and videos that illustrate real-world events. It describes scraping various event directories and linking the data. Media can be found by searching based on geo-tags, titles, or uploader. Visual analysis is used to prune media results. The goal is to help users explore, annotate and share media related to events. Challenges include interlinking diverse data sources and detecting unscheduled events.
Europeana and the relevance of the DM2E resultsAntoine Isaac
Presentation on the value of results of the DM2E project, from the Europeana perspective.
Presented at the DM2E final event, Pisa, Dec 11 2014
http://dm2e.eu/dm2e-final-event-registration-and-agenda/
Data modelling at Europeana and DM2E - SMW13Antoine Isaac
Presentation on how the Eduorpeana Data Model is used and extended in the Europeana and DM2E projects.
Made for the Semantic Media Web innovation day, Berlin, Sept 27, 2013: http://semantic-media-web.de/innovationsforum/metadaten/
Implementing the Media Fragments URI SpecificationRaphael Troncy
Implementing the Media Fragments URI Specification - Talk given at the Developer's Track of the 19th World Wide Web Conference (WWW'2010), Raleigh (NC), USA, April 29th 2010
Wikidata, a target for Europeana's semantic strategy - GLAM-WIKI 2015Antoine Isaac
"Wikidata, a target for Europeana's semantic strategy"/ Presentation at the GLAM-Wiki conference with Valentine Charles, Hugo Manguinhas, Antoine Isaac, Vladimir Alexiev http://nl.wikimedia.org/wiki/GLAM-WIKI_2015/
This document summarizes the progress made by the National Information Standards Organization (NISO) in developing standards for new metrics in scholarship, known as altmetrics. It discusses how NISO held discussions and meetings with over 400 contributors to brainstorm ideas and reach consensus on key elements needed to build trust in metrics, including defining what is counted, how it is identified, aggregation procedures, and data exchange standards. The goal is to establish standardized approaches and definitions that can facilitate consistent measurement and comparison of the broader impacts of scholarly work.
Todd Carpenter's presentation at the Electronic Resources in Libraries (ER&L) conference in Austin, TX, February 23, 2015. Todd discussed how new forms of assessment are entering the mainstream and how those metrics shouldn't be considered "alternative" any longer. The session also covered the advancements made in 2014 on the NISO Alternative Assessment initiative, that was generously funded by the Alfred P. Sloan Foundation.
Transcript - DOIs to support citation of grey literatureARDC
24th May 2017
This webinar was the first in a series examining persistent identifiers and their use in research. It begins with a brief introduction on the use of persistent identifiers in research followed by an outline of how UNSW has approached supporting discovery and citation of grey literature.
Watch the full webinar: https://www.youtube.com/watch?v=TLXYwrBu8wc
Data Innovation Lens: A New Way to Approach Data Design as Value CreationAleksi Aaltonen
Presentation at the London School of Economics and Political Science on May 10, KIN Center for Digital Innovation, Amsterdam on May 7, and at ESSEC Business School, Paris on April 30, 2024 on the study of data as innovation. The presentation is based on a paper coauthored with Marta Stelmaszak.
Getting started in Data Science (April 2017, Los Angeles)Thinkful
The document discusses the rise of data science and the skills needed for data scientists. It defines data science as the intersection of engineering, statistics, and communication. Data scientists analyze large datasets to answer important business questions. The document uses LinkedIn in 2006 as a case study, outlining how a data scientist there framed questions, collected and processed user data, explored patterns, and communicated results to improve the user experience and growth. It highlights tools like SQL, analytics software, and machine learning that data scientists use and stresses the importance of curiosity, technical skills, and strong communication for those interested in the field.
ODIN Final Event - Publishing and citing, and the role of persistent identifiersdatacite
Sünje Dallmeier-Tiessen
CERN
Presentation delivered at the ODIN Final Event in Amsterdam (Netherlands) on Wednesday, September 24, 2014: ORCID and DataCite: Towards Holistic Open Research.
More info: www.odin-project.eu
This document discusses issues related to attributing and citing scientific data. It addresses technical, scientific, institutional, and socio-cultural challenges. Key questions are outlined regarding data citation standards and practices. The roles of different actors in the research enterprise are also discussed. Effective data attribution requires consideration of provenance, ethics, discoverability, relationships between data, intellectual property issues, and policies. Metrics for data use must be grounded in scientific theory to ensure their validity and reliability.
This document discusses reputation and how it is measured in academia. It outlines that reputation is comprised of publication performance, institutional performance, and researcher performance. Publication performance is increasingly being measured through article-level metrics and altmetrics. Institutional performance is assessed through frameworks like the UK Research Excellence Framework. Researcher performance encompasses numerous factors like publications, funding, and affiliations. The document predicts that scoring and reward systems for academic activities will emerge, along with complex algorithms to assess impact, and tools that can influence performance metrics.
This document discusses how libraries can leverage linked data and real world objects to provide more context for users. It suggests that libraries can link catalog records to related resources outside their collections, such as different editions, title changes for serials, and other resources about people, places, and subjects. This builds relationships between library data and the larger web of data to better support users in finding, identifying, selecting, obtaining, and exploring information.
This document provides an overview of data science including its importance, what data scientists do, how the field has emerged, and how to become a data scientist. It discusses how data science can help answer important business questions using LinkedIn in 2006 as a case study. It also outlines the typical data science process of framing questions, collecting and cleaning data, exploring patterns, and communicating results. Finally, it introduces some common data science tools like SQL, analytics software, and machine learning algorithms and discusses options for continuing education in data science.
You've heard the news, Data Science is the cool new career opportunity sweeping the world. Come learn from Thinkful Mentors all about this new and exciting industry.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
This document summarizes the Library Impact Data Project, which aimed to show correlations between library usage data (books borrowed, e-resources accessed) and student attainment across multiple universities. Phase 1 found statistical significance between library usage and grades. Phase 2 added more student data points and found further correlations with demographics. The project aims to create a shared analytics service to allow libraries to analyze usage and benchmark against peers. Key areas for the next phase include developing an intuitive dashboard, addressing ethical issues around profiling individuals, and integrating additional data sources.
This document provides an overview of data science including its importance, what data scientists do, how the field has emerged, and how to become a data scientist. It notes that by 2018 the US could face shortages of people with data analytics skills. It then discusses how LinkedIn's early growth in 2006 exemplifies the data science process of framing questions, collecting and processing data, exploring patterns, and communicating results. Finally, it outlines the tools used in data science like SQL, analytics software, and machine learning and discusses getting started in the field through education, curiosity, and ongoing learning with mentorship support.
Social CI: A Work method and a tool for Competitive Intelligence NetworkingComintelli
This presentation is from a webinar hosted by Comintelli and is a part of a project called CIBAS: a collaboration with the Department of Media Technology at Södertörn University in Stockholm, Sweden. A new notion called social CI is introduced, meaning competitive intelligence (CI) for the networking organization. A conceptual framework for social CI is presented that is based on a socio-technical perspective combining both social and technical aspects. The presented framework is related to notions such as Enterprise 2.0 and wikinomics. A research design prototype of a tool for collaborative CI, CoCI, is also demonstrated. CoCI is a tool that has been developed using the Social CI framework that demonstrates how CI methods and CI tools can be developed together using a socio-technical approach.
Impact of DDOD on Data Quality - White House 2016David Portnoy
"The Impact of Demand-Driven Open Data (DDOD) on Data Quality" was presented on April 27, 2016 at Open Data Roundtable held at the White House Office of Science and Technology Policy.
It discusses the data quality problems prevalent in open data and their impact, the origins of the DDOD concept, how it works, progress towards its goals, several use case examples, and how to implement it at other organizations.
More information:
* DDOD http://ddod.healthdata.gov
* Open Data Roundtables https://www.data.gov/meta/open-data-roundtables/
* White House Office of Science and Technology Policy: https://www.whitehouse.gov/blog/2016/02/05/open-data-empowering-americans-make-data-driven-decisions
If Data Are The New Oil, How Do We Prevent Global Warming?Philip Bourne
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1. The Infrastructure for
Alternative Metrics
What do we need to compare
digital apples to digital apples?
!
Todd Carpenter, Executive Director, NISO
AAAS Annual Meeting
Chicago, IL | February 16, 2014
4. About
•
Non-profit industry trade association accredited
by ANSI with 190+ members
•
Mission of developing and maintaining technical
standards related to information, documentation,
discovery and distribution of published materials
and media
•
Volunteer driven organization: 400+ spread out
across the world
•
Responsible in various wasy for standards like
ISSN, DOI, Dublin Core metadata, DAISY digital
talking books, OpenURL, MARC records, and ISBN
5. Photo by dumbledad on Flickr http://www.flickr.com/photos/dumbledad/298650884/!
6. But what is the
“infrastructure” for
assessment?
16. A simple conclusion
can be drawn
Citations are awesome, aren’t they?
A perfect solution to all the world’s
problems, no?
17. Back to Sir Isaac Newton
“What Des-Cartes did
was a good step.You have
added much several
ways, & especially in
taking ye colours of thin
plates into philosophical
consideration. If I have
seen further it is by
standing on ye shoulders
of Giants."
35. Consistency in what is counted
Source:
Scott
Chamberlain,
Consuming
Article-‐Level
Metrics:
Observations
And
Lessons
From
Comparing
Aggregator
Provider
Data,
Information
Standards
Quarterly,
Summer
2013,
Vol
25,
Issue
2.
49. Alterna(ve
Assessment
Ini(a(ve
!
Phase
1
Mee(ngs
October
9,
2013
-‐
San
Francisco,
CA
December
11,
2013
-‐
Washington,
DC
January
23-‐24
-‐
Philadelphia,
PA
!
Phase
1
report
expected
in
May
2014
50. Just
a
few
ideas
from
in-‐person
mee(ngs
Disambigua)on
problems
Create
a
central
repository
for
data
Define
provenance
for
metrics
Foster
culture
of
DOI
use
in
mass
media
Establish
defini)ons
for
metric
types
Define
data
extract/gathering
methods
Standardize
units
of
measure
Define
levels
of
transparency/privacy
!
51. Alterna(ve
Assessment
Ini(a(ve
!
Phase
2
Presenta(ons
of
report
(June
2014)
Priori(za(on
Effort
(June
-‐
Aug,
2014)
Project
approval
(Sept
2014)
Working
group
forma(on
(Oct
2014)
Consensus
Development
(Nov
2014
-‐
Dec
2015)
Trial
Use
Period
(Dec
15
-‐
Mar
16)
Publica(on
of
final
recommenda(ons
(Jun
16)