eROSA Stakeholder WS1: Big Data and Open Science in agricultural and environm...e-ROSA
This document discusses challenges and opportunities around big data and open science in agricultural and environmental research. It provides a historic perspective on the evolution of data and modeling capabilities over time. While new technologies promise to make data access and analysis easier, realities often involve continuing to use existing approaches and hybrid solutions. The document recommends a focus on improving methodologies to semantically link diverse data sources. Adopting open science practices will require changes to research culture as well as technologies. The workshop aims to discuss needed services and integration across generic and domain-specific research infrastructures to advance open science in agriculture.
This document summarizes efforts to develop active, machine-actionable data management plans (DMPs). It discusses the vision of transforming static DMPs into dynamic documents that can be automatically processed by systems to help researchers, institutions, and funders. It outlines various initiatives exploring technical standards and platforms to make DMPs interoperable and leverage identifiers. These include workshops discussing use cases, a white paper on common approaches, and groups developing shared principles and specifications. The document provides an overview of the technical landscape and opportunities for stakeholders to engage and contribute to ongoing work.
UCL & IoE Libraries - Research Data Management - 22/10/14Caroline Lloyd
This document summarizes initiatives between the libraries of UCL and IOE including exchanges of staff and expertise on topics like research data management, open access, and user satisfaction. It also outlines workshops between the two libraries on research data management, big data, and setting three action points. The workshops discuss challenges and existing services for researchers and libraries regarding research data and big data, and how libraries can be involved with stakeholders.
Revolutionising the Journal through Big Data Computational ResearchAmye Kenall
BioMed Central is an open access publisher that publishes over 260 journals annually covering fields like genomics, computational biology, and public health. The document discusses BioMed Central's efforts to revolutionize journals through encouraging data reuse and reproducibility in computational research. This includes providing datasets used in articles, applying DOIs to additional files to improve searchability and citation, and exploring options like interactive tabular data and virtual machines to facilitate replicating analyses. Challenges discussed include balancing included versus external data sizes, dataset versioning, and encouraging author data sharing.
The document discusses the European Open Science Cloud which aims to provide researchers seamless access to advanced digital resources and expertise needed for collaboration and data-intensive science. It presents a potential architecture for the Open Science Cloud including basic infrastructure, common services, federation services, and added value services to support communities. The architecture is meant to engage researchers and govern resources for everyone's benefit.
This document discusses the challenges and goals of the EOSCpilot project, which aims to support the development of the European Open Science Cloud (EOSC). The EOSCpilot will work to establish an EOSC governance framework, develop science demonstrators to showcase interoperability across domains, and engage stakeholders to build trust and skills for open science. It will also address technical, scientific, and cultural challenges to deploying the EOSC and adopting more open ways of working. The overall goals are to make scientific data open by default, improve data sharing incentives, develop interoperability specifications, and create a pan-European governance structure to overcome fragmentation.
RDN Lightning talk - Open Research Leeds (@OpenResLeeds): networks, metrics a...Nick Sheppard
This document discusses the use of social media and open access to increase the impact and discoverability of research. It notes that simply making research available online is not enough and additional promotion is needed. It provides examples of metrics and tools to track the usage and dissemination of research articles and datasets, including altmetrics, IRUS-UK, and Figshare. The importance of using hashtags and engaging on social media platforms like Twitter to promote research is also emphasized.
eROSA Stakeholder WS1: Big Data and Open Science in agricultural and environm...e-ROSA
This document discusses challenges and opportunities around big data and open science in agricultural and environmental research. It provides a historic perspective on the evolution of data and modeling capabilities over time. While new technologies promise to make data access and analysis easier, realities often involve continuing to use existing approaches and hybrid solutions. The document recommends a focus on improving methodologies to semantically link diverse data sources. Adopting open science practices will require changes to research culture as well as technologies. The workshop aims to discuss needed services and integration across generic and domain-specific research infrastructures to advance open science in agriculture.
This document summarizes efforts to develop active, machine-actionable data management plans (DMPs). It discusses the vision of transforming static DMPs into dynamic documents that can be automatically processed by systems to help researchers, institutions, and funders. It outlines various initiatives exploring technical standards and platforms to make DMPs interoperable and leverage identifiers. These include workshops discussing use cases, a white paper on common approaches, and groups developing shared principles and specifications. The document provides an overview of the technical landscape and opportunities for stakeholders to engage and contribute to ongoing work.
UCL & IoE Libraries - Research Data Management - 22/10/14Caroline Lloyd
This document summarizes initiatives between the libraries of UCL and IOE including exchanges of staff and expertise on topics like research data management, open access, and user satisfaction. It also outlines workshops between the two libraries on research data management, big data, and setting three action points. The workshops discuss challenges and existing services for researchers and libraries regarding research data and big data, and how libraries can be involved with stakeholders.
Revolutionising the Journal through Big Data Computational ResearchAmye Kenall
BioMed Central is an open access publisher that publishes over 260 journals annually covering fields like genomics, computational biology, and public health. The document discusses BioMed Central's efforts to revolutionize journals through encouraging data reuse and reproducibility in computational research. This includes providing datasets used in articles, applying DOIs to additional files to improve searchability and citation, and exploring options like interactive tabular data and virtual machines to facilitate replicating analyses. Challenges discussed include balancing included versus external data sizes, dataset versioning, and encouraging author data sharing.
The document discusses the European Open Science Cloud which aims to provide researchers seamless access to advanced digital resources and expertise needed for collaboration and data-intensive science. It presents a potential architecture for the Open Science Cloud including basic infrastructure, common services, federation services, and added value services to support communities. The architecture is meant to engage researchers and govern resources for everyone's benefit.
This document discusses the challenges and goals of the EOSCpilot project, which aims to support the development of the European Open Science Cloud (EOSC). The EOSCpilot will work to establish an EOSC governance framework, develop science demonstrators to showcase interoperability across domains, and engage stakeholders to build trust and skills for open science. It will also address technical, scientific, and cultural challenges to deploying the EOSC and adopting more open ways of working. The overall goals are to make scientific data open by default, improve data sharing incentives, develop interoperability specifications, and create a pan-European governance structure to overcome fragmentation.
RDN Lightning talk - Open Research Leeds (@OpenResLeeds): networks, metrics a...Nick Sheppard
This document discusses the use of social media and open access to increase the impact and discoverability of research. It notes that simply making research available online is not enough and additional promotion is needed. It provides examples of metrics and tools to track the usage and dissemination of research articles and datasets, including altmetrics, IRUS-UK, and Figshare. The importance of using hashtags and engaging on social media platforms like Twitter to promote research is also emphasized.
Incremental adaptive semi-supervised fuzzy clustering for data stream classif...Gabriella Casalino
Presentation of the article "Incremental adaptive semi-supervised fuzzy clustering for data stream classification" at the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018), Rhodes 25-29 May 2018
Joint work with Giovanna Castellano and Corrado Mencar
EDF2014: Vedran Sabol, Head of the Knowledge Visualisation Area, Know-Center,...European Data Forum
The document summarizes the CODE project which aims to establish a web-based ecosystem for linked open data in research. It describes CODE services for semantic enrichment of research papers and creating RDF data cubes. It also outlines three application scenarios - semantic mindmaps, semantic research papers, and 42-Data, a data-centric discussion forum and marketplace. 42-Data aims to socialize research data by allowing data-centric discussions, data sharing and transactions on small datasets.
WikiRate - Data Liberation and Radical TransparencyVishal Kapadia
WikiRate.org responds to the problem of siloed and trapped data around company CSR reporting with an open source, public platform, which allows anyone to utilise and analyse the data.
This presentation will discuss how the structured data, together with the semantically indexed/mined entities in semi-structured and unstructured data, are contributing to researches beyond libraries, especially in digital humanities. It aims to explore the opportunities and strategies to use, reuse, share, and effectively elaborate the smart data -- generated or to be generated -- in libraries.
FP7 OpenCube project presentation at NTTS 2015 conferenceEfthimios Tambouris
FP7 OpenCube project presentation at New Techniques and Technologies for Statistics (NTTS) conference. The conference took plance at Brussels between 10 and 12 March 2015.
This document proposes a 10-minute presentation about Mendeley, a research collaboration tool that extracts metadata from papers and allows researchers to organize, annotate, and collaborate on their work. Mendeley anonymously aggregates usage data to provide social metrics and insights into research trends. Within 18 months, Mendeley grew to over 400,000 users and 30 million research entries, on track to become the largest open academic database. It has overcome challenges to create a stable tool for large numbers of users and is working to further enrich its data through mining activities.
Think Big about Data: Archaeology and the Big Data Challengeariadnenetwork
Presentation by Gabriele Gattiglia, University of Pisa – MAPPA Lab
EAA 2014 session: Open Access and Open Data in Archaeology
Istanbul, Turkey
13 September 2013
FP7 Funded RI Project experiences: some overly honest tips from a project coo...Vince Smith
Smith, V.S. 2014. FP7 Funded RI Project experiences: some overly honest tips from a project coordinator, EC Horizon 2020 Research Infrastructures Information Day in at the Natural History Museum London, U.K. 18 June 2014.
Research data discovery in OpenAIRE (Presentation by Paolo Manghi at DI4R2018)OpenAIRE
"Research data discovery in OpenAIRE".
Presentation by Paolo Manghi from CNR-ISTI, at the Digital Infrastructures Conference 2018, Lisbon. Session: Building better collaborative national networks to support Open Science (Oct. 11, 2018)
Special Issue on: "Advances in Neural Network Models and Algorithms for Data ...gerogepatton
Recent advances in storage, hardware, information technology, communication, and networking have resulted in increasingly large and complex heterogeneous data. This has powered the demand to extract useful and actionable insights from data in an automatic, reliable and scalable way. Neural networks are widely used learning machines with powerful learning ability and adaptability, which have achieved remarkable performance in the data analytical tasks, such as computer vision, face/speech recognition, video surveillance, document summarization, distributed and/or real-time resource allocation, etc. Recently there is a surge of research activities devoted to theoretical development of scalable and robust learning models on deep neural networks, neurodynamics, combinatorial optimization techniques.
Big Data R&D Strategy - Ensure the long term sustainability, access, and deve...Sky Bristol
Presentation on one of the strategic themes being considered for a U.S. Government Big Data R&D strategy - https://www.nitrd.gov/bigdata/rfi/02102014.aspx.
The OpenAIRE Research Graph aims to provide an open metadata research graph of interlinked scientific products with open access information linked to funding and communities. It harvests data from various sources to populate a graph of over 340 million records, 12 million publications, and 960 million links. The graph brings scholarly communication back into researchers' hands by making metadata and resources complete, de-duplicated, transparent, participatory, decentralized, and trusted. OpenAIRE seeks feedback to improve the beta version and plans to launch the full research graph in Spring 2020.
Mendeley is a research collaboration tool that allows scientists to organize papers, take notes, and view metrics on papers' usage. It extracts metadata from papers and enables researchers to annotate and tag papers. This creates a social network where researchers can see trends and collaborate. Mendeley has grown to nearly 1 million users and over 80 million documents, making it the largest crowdsourced academic database. It helps researchers by making papers social objects that can be discussed and adding semantic information to papers through annotations.
OpenAIRE2020, the latest project phase of the OpenAIRE initiative, ends in mid-2018. Yet OpenAIRE will live on as a sustainable legal entity and anticipates continuing to shape the conversation on Open Science implementation in Europe and beyond. This talk will briefly present OpenAIRE's achievements since 2008 and lay out our future priorities for Open Science, including: continued expansion of services from Open Access to Open Science and from Publications to all research artefacts; services for research data management at all levels from local to global; Open Science monitoring and research analytics; engaging researchers and research infrastructures with personalisable services.
This document summarizes an OpenAIRE stakeholder workshop that took place in Athens on May 21-22, 2018. OpenAIRE supports open science by monitoring research outputs, accelerating interoperability and exchange, and supporting researchers and infrastructure providers through services like an open science helpdesk and research data management support. The workshop discussed OpenAIRE's network of National Open Access Desks, services to support open policies, infrastructure, open research data and open access publications, and efforts to build an open scholarly communication graph and research information system. OpenAIRE also presented services for content providers like the PROVIDE Dashboard for validation, enrichment and usage statistics of metadata.
This document summarizes a research project aimed at increasing the visibility and discoverability of thesis data through the use of persistent identifiers (PIDs). The project is a collaboration between several UK universities and involves conducting case studies and a survey to evaluate current practices around PIDs. The next phase will involve hosting clinics for universities wanting to implement PIDs and engaging with repository communities to develop a national solution for assigning PIDs to thesis data.
This document provides an update on ORCID and discusses its growing membership. ORCID now has over 2.2 million iDs, 500+ members, and 6 national and 4 regional consortia. Research organizations make up the largest percentage of ORCID membership at 65%. Europe accounts for the largest regional membership at 53%. ORCID iDs are increasingly being required for publishing in journals from several major publishers. ORCID also continues to expand its auto-update features to keep member profiles and data up-to-date.
Incremental adaptive semi-supervised fuzzy clustering for data stream classif...Gabriella Casalino
Presentation of the article "Incremental adaptive semi-supervised fuzzy clustering for data stream classification" at the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018), Rhodes 25-29 May 2018
Joint work with Giovanna Castellano and Corrado Mencar
EDF2014: Vedran Sabol, Head of the Knowledge Visualisation Area, Know-Center,...European Data Forum
The document summarizes the CODE project which aims to establish a web-based ecosystem for linked open data in research. It describes CODE services for semantic enrichment of research papers and creating RDF data cubes. It also outlines three application scenarios - semantic mindmaps, semantic research papers, and 42-Data, a data-centric discussion forum and marketplace. 42-Data aims to socialize research data by allowing data-centric discussions, data sharing and transactions on small datasets.
WikiRate - Data Liberation and Radical TransparencyVishal Kapadia
WikiRate.org responds to the problem of siloed and trapped data around company CSR reporting with an open source, public platform, which allows anyone to utilise and analyse the data.
This presentation will discuss how the structured data, together with the semantically indexed/mined entities in semi-structured and unstructured data, are contributing to researches beyond libraries, especially in digital humanities. It aims to explore the opportunities and strategies to use, reuse, share, and effectively elaborate the smart data -- generated or to be generated -- in libraries.
FP7 OpenCube project presentation at NTTS 2015 conferenceEfthimios Tambouris
FP7 OpenCube project presentation at New Techniques and Technologies for Statistics (NTTS) conference. The conference took plance at Brussels between 10 and 12 March 2015.
This document proposes a 10-minute presentation about Mendeley, a research collaboration tool that extracts metadata from papers and allows researchers to organize, annotate, and collaborate on their work. Mendeley anonymously aggregates usage data to provide social metrics and insights into research trends. Within 18 months, Mendeley grew to over 400,000 users and 30 million research entries, on track to become the largest open academic database. It has overcome challenges to create a stable tool for large numbers of users and is working to further enrich its data through mining activities.
Think Big about Data: Archaeology and the Big Data Challengeariadnenetwork
Presentation by Gabriele Gattiglia, University of Pisa – MAPPA Lab
EAA 2014 session: Open Access and Open Data in Archaeology
Istanbul, Turkey
13 September 2013
FP7 Funded RI Project experiences: some overly honest tips from a project coo...Vince Smith
Smith, V.S. 2014. FP7 Funded RI Project experiences: some overly honest tips from a project coordinator, EC Horizon 2020 Research Infrastructures Information Day in at the Natural History Museum London, U.K. 18 June 2014.
Research data discovery in OpenAIRE (Presentation by Paolo Manghi at DI4R2018)OpenAIRE
"Research data discovery in OpenAIRE".
Presentation by Paolo Manghi from CNR-ISTI, at the Digital Infrastructures Conference 2018, Lisbon. Session: Building better collaborative national networks to support Open Science (Oct. 11, 2018)
Special Issue on: "Advances in Neural Network Models and Algorithms for Data ...gerogepatton
Recent advances in storage, hardware, information technology, communication, and networking have resulted in increasingly large and complex heterogeneous data. This has powered the demand to extract useful and actionable insights from data in an automatic, reliable and scalable way. Neural networks are widely used learning machines with powerful learning ability and adaptability, which have achieved remarkable performance in the data analytical tasks, such as computer vision, face/speech recognition, video surveillance, document summarization, distributed and/or real-time resource allocation, etc. Recently there is a surge of research activities devoted to theoretical development of scalable and robust learning models on deep neural networks, neurodynamics, combinatorial optimization techniques.
Big Data R&D Strategy - Ensure the long term sustainability, access, and deve...Sky Bristol
Presentation on one of the strategic themes being considered for a U.S. Government Big Data R&D strategy - https://www.nitrd.gov/bigdata/rfi/02102014.aspx.
The OpenAIRE Research Graph aims to provide an open metadata research graph of interlinked scientific products with open access information linked to funding and communities. It harvests data from various sources to populate a graph of over 340 million records, 12 million publications, and 960 million links. The graph brings scholarly communication back into researchers' hands by making metadata and resources complete, de-duplicated, transparent, participatory, decentralized, and trusted. OpenAIRE seeks feedback to improve the beta version and plans to launch the full research graph in Spring 2020.
Mendeley is a research collaboration tool that allows scientists to organize papers, take notes, and view metrics on papers' usage. It extracts metadata from papers and enables researchers to annotate and tag papers. This creates a social network where researchers can see trends and collaborate. Mendeley has grown to nearly 1 million users and over 80 million documents, making it the largest crowdsourced academic database. It helps researchers by making papers social objects that can be discussed and adding semantic information to papers through annotations.
OpenAIRE2020, the latest project phase of the OpenAIRE initiative, ends in mid-2018. Yet OpenAIRE will live on as a sustainable legal entity and anticipates continuing to shape the conversation on Open Science implementation in Europe and beyond. This talk will briefly present OpenAIRE's achievements since 2008 and lay out our future priorities for Open Science, including: continued expansion of services from Open Access to Open Science and from Publications to all research artefacts; services for research data management at all levels from local to global; Open Science monitoring and research analytics; engaging researchers and research infrastructures with personalisable services.
This document summarizes an OpenAIRE stakeholder workshop that took place in Athens on May 21-22, 2018. OpenAIRE supports open science by monitoring research outputs, accelerating interoperability and exchange, and supporting researchers and infrastructure providers through services like an open science helpdesk and research data management support. The workshop discussed OpenAIRE's network of National Open Access Desks, services to support open policies, infrastructure, open research data and open access publications, and efforts to build an open scholarly communication graph and research information system. OpenAIRE also presented services for content providers like the PROVIDE Dashboard for validation, enrichment and usage statistics of metadata.
This document summarizes a research project aimed at increasing the visibility and discoverability of thesis data through the use of persistent identifiers (PIDs). The project is a collaboration between several UK universities and involves conducting case studies and a survey to evaluate current practices around PIDs. The next phase will involve hosting clinics for universities wanting to implement PIDs and engaging with repository communities to develop a national solution for assigning PIDs to thesis data.
This document provides an update on ORCID and discusses its growing membership. ORCID now has over 2.2 million iDs, 500+ members, and 6 national and 4 regional consortia. Research organizations make up the largest percentage of ORCID membership at 65%. Europe accounts for the largest regional membership at 53%. ORCID iDs are increasingly being required for publishing in journals from several major publishers. ORCID also continues to expand its auto-update features to keep member profiles and data up-to-date.
The Research Councils UK (RCUK) has recently launched the ability for applicants to create and connect their ORCID iD to their grants system. By the end of the summer, RCUK expects to publish ORCID iDs against research information in their public Gateway to Research database. RCUK is working to improve interoperability between ORCID and other research systems like ResearchFish to enable exchange of publication data and reduce duplication for researchers. However, RCUK must also limit changes to their current grants system as they build a new one.
Stakeholder forum 2015 - The way forward together - Phil RichardsJisc
This document outlines an agenda for a stakeholder forum on moving forward together. It includes sections on research and development pipelines at Jisc, ensuring radical innovation, and group exercises. Upcoming and current projects are briefly described, such as an online tool for participant recruitment, a kit cataloguing system, and tools to analyze higher education datasets. Risk distribution strategies for future projects and the need for bold ideas beyond incremental changes are also mentioned. The document concludes with a list of breakout group topics for the stakeholder forum.
La Unión Europea ha acordado un paquete de sanciones contra Rusia por su invasión de Ucrania. Las sanciones incluyen restricciones a los bancos rusos, la prohibición de la venta de aviones y equipos a Rusia, y sanciones contra funcionarios rusos. Los líderes de la UE esperan que las sanciones aumenten la presión económica sobre Rusia y la disuadan de continuar su agresión contra Ucrania.
My Self+Name,Nickname, Age+ป.1+104+dltvengp1+54en p01 f23-4pagePrachoom Rangkasikorn
The document contains basic conversational phrases and counting in Thai. It introduces greetings like hello and how are you, asks and provides a name, counts from one to ten, and repeats phrases for practice.
1) Latvia's largest computer literacy project for senior citizens called "Connect, Latvia" aims to reduce the digital divide and social exclusion among seniors aged 55-74, many of whom have never used the internet before.
2) The project, led by Lattelecom, provides a three-tiered computer training course taught in Latvian and Russian in 96 out of 119 municipalities, with groups of up to 14 seniors that meet for three days of four hours each.
3) Over six years, the program has helped 28,080 senior citizens in Latvia acquire basic computer and internet skills, helping to address unemployment and poverty risks among pre-retirement age groups.
The document provides production information for a photo shoot of a band. It lists the nearest hospital to the set location as the One Life Centre in Hartlepool. It includes a call sheet with details of the scene, cast, and schedule for a single day shoot featuring the band. Props include a guitar amp and microphone, and wardrobe requires casual wear.
The european commission's current agenda on personal and household services ...CARER+ Project
This document summarizes a conference on personal and household services held in Paris in 2015. It discusses how personal and household services can help address issues related to work-life balance, job creation, and care services. It notes initiatives by the European Commission to support this sector through projects on measurement, quality, and efficiency. These projects aim to improve understanding of the employment and budget impacts of public support, promote quality jobs and standards, and analyze productivity gains and new technologies.
Smart homecare fine tuning professional and family care- zelderlooCARER+ Project
The document discusses pathways to future support models in social services for persons with disabilities in Europe. It outlines that personal and household services are a positive step but quality must be guaranteed. It also notes that demand for social and health services is growing while supply is diminishing. Finally, it proposes that the future will see a partnership between families and professional support providers, with empowered families becoming employers and new funding shifting power dynamics, enabled by technology.
This document proposes a system to give researchers credit for depositing their data by allowing them to easily submit a "data paper" about their deposited data set. It involves developing a helper application that would integrate with data repositories and publishers to streamline the process of depositing data and submitting the associated data paper. The proposal outlines three phases: requirements gathering and design, development and trial deployment, and expansion and sustainability. The goal is to incentivize data sharing by providing researchers a publication and citation opportunity for describing and taking credit for their datasets.
This document provides an introduction to research. It discusses why research is important, including gaining new knowledge to improve patient care and making evidence-based decisions. It outlines the typical steps in a research process, including identifying a research area and question, developing a research design with a study population and sampling plan, collecting and analyzing data, and publishing and sharing findings. It also describes different types of research such as experimental, prevalence, cross-sectional, and correlational studies. The document encourages curiosity as the essence of research and offers suggestions for how to start the research process.
The document discusses various primitive data types including integer, floating point, decimal, boolean, and character. It describes the evolution of character encoding from EBCDIC to ASCII to Unicode. It also covers string operations and different implementations of strings in languages. The document discusses ordinal types like enumeration and subrange. It provides details about array types including static, dynamic, and associative arrays. It compares array implementations across languages.
Dokumen tersebut berisi soal-soal tes pilihan ganda dari berbagai bidang studi fisika, seperti mekanika, termodinamika, gelombang, dan elektromagnetisme. Terdapat 30 pertanyaan yang mencakup konsep-konsep dasar fisika.
ocial support and long term care for older people – GhentaCARER+ Project
This document summarizes a conference presentation on social support and long-term care for older people. It discusses the objectives of researching potentials for social innovation and active aging. Key points included analyzing the current state of long-term care across different countries, identifying drivers and barriers to social innovation, and providing indicators for future active aging scenarios. The presentation also covered defining active aging and long-term care, differences in long-term care systems across European countries, and factors influencing social innovation initiatives in long-term care.
Collaboration through technology: moving from possibility to practice - Mar...Jisc
This session will explore the potential that technology can bring to all forms of collaboration, and consider the difference that it has made to some local organisations and their practices.
Martin Hamilton, Jisc and Kerry Harrison, Burnley College
Connect more in Liverpool, 21 June 2016.
Managing 'Big Data' in the social sciences: the contribution of an analytico-...CILIP MDG
This document discusses managing large datasets in the social sciences. It describes how the UK Data Service curates and provides access to large survey and census data. It explores how classification schemes could help organize and provide subject access to these growing datasets. A pilot project classified datasets using the Universal Decimal Classification scheme and found it efficient and helped visualize subject categories. Overall, carefully chosen knowledge organization tools can help provide multidimensional subject access needed to analyze complex datasets.
Enabling complex analysis of large scale digital collectionsJisc
This document summarizes a project to enable complex analysis of large digitized collections through expanded research data management. The project has successfully implemented complex searches of 64,000 digitized books from the British Library. In the next phase, the project will scale up by adding additional data sources, working with more researchers to understand their needs, and training researchers and librarians to independently query the data. The goal is to make digitized collections truly searchable and support novel research in the arts, humanities, and social sciences.
Organizational Implications of Data Science Environments in Education, Resear...Victoria Steeves
Data science (DS) poses key organizational challenges for academic institutions. DS is a multidisciplinary field that includes a range of research methodologies and fields of inquiry. DS as a domain is interested in many of the same issues as libraries: data access and curation, reproducibility, the value of ontologies, and open scholarship. At the same time, identifying opportunities to collaborate and deploy unified services can be challenging. The Data Science Environment (DSE) program, co-funded by the Gordon and Betty Moore and Alfred P. Sloan foundations, provides resources to help universities develop collaborations between researchers, develop tools in DS, and create new career paths for data scientists. Working groups within the DSE focus on reproducibility, career paths, education/training, research methods, space issues, and software/tools. This program has introduced new opportunities for libraries to explore how to engage with this community and consider how to bring the expertise in the DS community to bear on library missions and goals. In this panel, program members from each of the three partner universities, the University of Washington, New York University and the University of California, Berkeley, consider the research questions of the DSE and the organizational impact of these groups in the University as a whole and for the libraries specifically. The panel will employ a case-study presentation model framed through three lenses: the role of data sciences in information science, the
potential career paths for data scientists in libraries, and the potential
amplification of information services (e.g. data curation, institutional repositories, scholarly publishing).
CNI Program: Talk Description: https://www.cni.org/topics/digital-curation/organizational-implications-of-data-science-environments-in-education-research-and-research-management-in-libraries
Video of Talk--Vimeo: https://vimeo.com/149713097
Video of Talk--YouTube: https://www.youtube.com/watch?v=L0G9JsPMEXY
This document discusses the need for digital curation specialists in library settings to manage the growing volume of scholarly data and output. It recognizes that libraries have the skills and infrastructure to curate digital resources but will need new roles like digital curators, archivists, and data scientists. These roles require new training programs and concentrations in areas like data curation to develop specialists that can preserve, organize, and provide access to digital collections over the long term.
Jabes 2021 - Poster "Bibliothèques de recherche - Compétences en science ouve...ABES
Poster présenté par l'association LIBER (conception Cécile Swiatek, groupe Digital skills for library staff and researchers).
Ce poster montre les parcours de compétences, les formations et des études de cas sélectives.
Immersive informatics - research data management at Pitt iSchool and Carnegie...Keith Webster
A joint presentation by Liz Lyon and Keith Webster on providing education for librarians engaged in research data management. This was delivered at Library Research Seminar VI, at the University of Illinois Urbana Champaign in September 2014. The presentation looks at a class delivered by Lyon at the University of Pittsburgh's iSchool in 2014, and the related needs for immersive training opportunities amongst experienced practicing librarians, using Carnegie Mellon University's library, led by Webster, as a case study.
Cuna Ekmekcioglu (University of Edinburgh) - “Engaging academic support libra...ARLGSW
Presentation from the 6th CILIP ARLG-SW Discover Academic Research and Training Support Conference (DARTS6). Dartington Hall, Totnes, Thursday 24th – Friday 25th May 2018
Digital research: Collections, data, tools and methods Stella Wisdom
Presentation for the Economic and Social Research Council North West Social Sciences Doctoral Training Partnership event on 26th November 2021, by Stella Wisdom, Digital Curator, British Library
Panel presentation given at: Policy and Technology for e-Science, ESOF (Euroscience Open Forum) Satellite Event, Institut d\'Estudis Catalans, Barcelona, Spain, 16-17 July 2008
for getting the library resources fro the libraries entire world, the important tool is Library catalogues. every can browse all most all the world literature through WorldCat fro the INTERNET.
In the last decade, several Scientific Knowledge Graphs (SKG) were released, representing scientific knowledge in a structured, interlinked, and semantically rich manner. But, what kind of information they describe? How they have been built? What can we do with them? In this lecture, I will first provide an overview of well-known SKGs, like Microsoft Academic Graph, Dimensions, and others. Then, I will present the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 21M publications and 8M patents according to i) the research topics drawn from the Computer Science Ontology, ii) the type of the author's affiliations (e.g, academia, industry), and iii) 66 industrial sectors (e.g., automotive, financial, energy, electronics) from the Industrial Sectors Ontology (INDUSO). Finally, I will showcase a number of tools and approaches using such SKGs, supporting researchers, companies, and policymakers in making sense of research dynamics.
Beyond Preservation: Situating Archaeological Data in Professional PracticeEric Kansa
This document discusses the potential for digital data in archaeology beyond just preserving existing practices. It outlines some visions, including optimizing current practices versus using data as an opportunity for new research methods and communication. Open Context is presented as taking the latter approach through open data sharing, linked data practices, and collaboration across projects. However, challenges to wider data sharing are also discussed, such as a lack of professional incentives and constraints of current academic evaluation systems. The document argues for treating data as an object of continued intellectual investment and innovation in order to fully realize its potential.
A 25 minute talk from a panel on big data curricula at JSM 2013
http://www.amstat.org/meetings/jsm/2013/onlineprogram/ActivityDetails.cfm?SessionID=208664
This document summarizes Nicole Vasilevsky's presentation on teaching data science to undergraduate students. It discusses the need for data science training, the open educational resources (OERs) developed by OHSU Library to address this need, and workshops offered including "Data and Donuts". The OERs cover the entire research process, from finding data to analysis to sharing results. Workshops are hands-on and interactive. Future plans include continuing "Data and Donuts" and potentially a larger OHSU Library Data Science Institute. The overall goal is to provide accessible data science training to address the growing demand.
PAARL's 1st Marina G. Dayrit Lecture Series held at UP's Melchor Hall, 5F, Proctor & Gamble Audiovisual Hall, College of Engineering, on 3 March 2017, with Albert Anthony D. Gavino of Smart Communications Inc. as resource speaker on the topic "Using Big Data to Enhance Library Services"
About the Webinar
Big data is being collected at a rate that is surpassing traditional analytical methods due to the constantly expanding ways in which data can be created and mined. Faculty in all disciplines are increasingly creating and/or incorporating big data into their research and institutions are creating repositories and other tools to manage it all. There are many challenge to effectively manage and curate this data—challenges that are both similar and different to managing document archives. Libraries can and are assuming a key role in making this information more useful, visible, and accessible, such as creating taxonomies, designing metadata schemes, and systematizing retrieval methods.
Our panelists will talk about their experience with big data curation, best practices for research data management, and the tools used by libraries as they take on this evolving role.
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Edinburgh DataShare: Tackling research data in a DSpace institutional repositoryRobin Rice
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3) The document recommends that institutions develop research data policies to clarify rights and responsibilities regarding data sharing and management.
The document discusses future developments in cognitive-based knowledge acquisition systems using big data. It covers preparing students and the cognitive landscape for big data analytics through tools like concept maps and visualization. It also addresses challenges like determining where information comes from, whether humans or computers can best identify patterns in data, and whether autonomous systems will eventually replace human decision making.
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Data science involves collecting, analyzing, and preserving large datasets to extract knowledge and make predictions. It differs from traditional disciplines by dealing with heterogeneous, unstructured data from complex networks. A data scientist requires math, computing, communication skills, and the ability to ask the right questions. Libraries are well-positioned to offer various data services including data discovery, consulting, mining, integration, and curation to support research and decision-making. Practicing data science in libraries requires vision, risk-taking, data science knowledge, careful planning, and collaboration.
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Enabling complex analysis of large scale digital collections
1. Research data spring
Enabling Complex Analysis of Large Scale Digital Collections27/2/2015
Lots of money has been spent digitising heritage
collections. Digitised heritage collections are data. But non-
computationally trained scholars don't know what to ask
of large quantities of data. Often they do not have access
to high performance computing facilities.
We aim to address this fundamental problem by
extending research data management processes in order
to enable novel research and a deeper understanding of
emerging research needs.
2. Team
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 2
James Baker
Curator, Digital
Research
Melissa Terras
Prof of Digital Humanities
David Beavan
Senior Research Associate
Martin Zaltz Austwick
Lecturer in Data
Visualisation
3. Scope and Gap
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 3
Non-computationally trained scholars don't know what
to ask of large quantities of digitised data
Large scale digitised collections are delivered in ad hoc
forms. Exemplar workflows for analysis of large scale
digitised collections are hard to find
Deploy and index large scale British Library (BL) digitised
collections at UCL Research IT Services (UCL RITS).
Work with researchers to turn their research questions
into computational analysis. Create and release
derived data, queries, and visualisations (that demonstrate
potential use) as citeable, CC-BY workflow packages
“I want to know
all the sentences
that mention
European cities
circa 1850 to
1900 in a BL
digitised texts
and take away
those results as a
data set”
4. Impact and Benefits
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 4
Outputs from phase one of the project would be used as
case studies and exemplars engage a wider community
and reduce research inefficiency
The project will generate engagement with new scholarly
communities around rich data resources
Narratives and workflows would be used in
interdisciplinary teaching at host institutions (Melissa:
MA/MSc Digital Humanities, Martin: BASc Arts and
Science, MRes Advanced Spatial Analysis and
Visualisation; James: BL Doctoral Training, MA History,
University of Kent)
5. Sustainability
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 5
Derived data, queries, documentation, and visualisations
released as citeable, CC-BY workflow packages with
DOIs (DataCite or Figshare)
Workflow packages embedded in teaching and
research training
Research computing communities beyond UCL deepen
understanding of complex, poorly structured, and
heterogeneous humanities data to enable process
improvement
Through BL Labs, university teaching, and BAU outreach
activities, narratives and lessons learned will have
substantial life beyond of the project
6. Outputs, milestones and indicators of success
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 6
To month 3:
● Deploy 68k digitised books (circa 4bn words!) at UCL
● Identify 3+ early career researchers (2 in hand)
● Run multi-day pilot workshop in partnership with all
parties, to work iteratively on data, workflow and
research questions
● Output: workflow packages, derived data,
visualisations to enable research insights
Social & technical barriers to analysis of large scale digitised collections are reduced
To month 7:
● Lead workshops and hackdays for the wider research community
● Deploy new BL datasets (based on researcher needs)
● Consolidate workflow packages and recipes
● Gather requirements for future infrastructure development (beyond scope of the
project)
To month 13:
● Recruit data
champions to drive
wider adoption of
methods
● Support community
led workshops
focussed on specific
domain needs and
challenges
● Create cookbook from
recepies
7. Funding
18/02/2015 Enabling Complex Analysis of Large Scale Digital Collections 7
To month 3:
UCL RITS Development: £5,500
Materials Development, Management and Administration: £10,025
Delivery of pilot workshops: £4,100
Total, full economic cost: £19,625