Scott Edmunds & Rob Davidson's talk at the Metabolomics Society 2014 Meeting on Beyond Dead Trees: data & workflow publishing with GigaScience, Tsuruoka 23rd June 2014
COMBINE 2019, EU-STANDS4PM, Heidelberg, Germany 18 July 2019
FAIR: Findable Accessable Interoperable Reusable. The “FAIR Principles” for research data, software, computational workflows, scripts, or any other kind of Research Object one can think of, is now a mantra; a method; a meme; a myth; a mystery. FAIR is about supporting and tracking the flow and availability of data across research organisations and the portability and sustainability of processing methods to enable transparent and reproducible results. All this is within the context of a bottom up society of collaborating (or burdened?) scientists, a top down collective of compliance-focused funders and policy makers and an in-the-middle posse of e-infrastructure providers.
Making the FAIR principles a reality is tricky. They are aspirations not standards. They are multi-dimensional and dependent on context such as the sensitivity and availability of the data and methods. We already see a jungle of projects, initiatives and programmes wrestling with the challenges. FAIR efforts have particularly focused on the “last mile” – “FAIRifying” destination community archive repositories and measuring their “compliance” to FAIR metrics (or less controversially “indicators”). But what about FAIR at the first mile, at source and how do we help Alice and Bob with their (secure) data management? If we tackle the FAIR first and last mile, what about the FAIR middle? What about FAIR beyond just data – like exchanging and reusing pipelines for precision medicine?
Since 2008 the FAIRDOM collaboration [1] has worked on FAIR asset management and the development of a FAIR asset Commons for multi-partner researcher projects [2], initially in the Systems Biology field. Since 2016 we have been working with the BioCompute Object Partnership [3] on standardising computational records of HTS precision medicine pipelines.
So, using our FAIRDOM and BioCompute Object binoculars let’s go on a FAIR safari! Let’s peruse the ecosystem, observe the different herds and reflect what where we are for FAIR personalised medicine.
References
[1] http://www.fair-dom.org
[2] http://www.fairdomhub.org
[3] http://www.biocomputeobject.org
JASM2014 talk - "Phinch: An interactive, exploratory data visualization for e...Holly Bik
Phinch is a web-based, interactive data visualization framework for analyzing environmental sequence data and metadata in standard formats like BIOM and tab-delimited files. It allows users to explore patterns in large datasets and export or share visualizations. Future work will add phylogenetic visualizations, more analysis tools, and an open source developer community to expand the framework's capabilities.
Reproducible and citable data and models: an introduction.FAIRDOM
Prepared and presented by Carole Goble (University of Manchester), Wolfgang Mueller (HITS), Dagmar Waltermath (University of Rostock), at the Reproducible and Citable Data and Models Workshop, Warnemünde, Germany. September 14th - 16th 2015.
Semantic Wiki Based Collaborative Scientific Modeling Infrastructure Jie Bao
This document describes a semantic wiki-based collaborative scientific modeling infrastructure that aims to support collaboration, hybrid modeling approaches, and accessibility. It allows users to publish and use scientific data through a wiki interface that integrates semantic technologies to enable formal modeling alongside informal text. The infrastructure provides concept modeling, policy modeling, group information management, and other applications to facilitate scientific collaboration and knowledge management.
Linked Data in a University Context: Publication, Applications and Beyond
The Open University (OU) is exposing its data as linked open data to make it more transparent, reusable and discoverable both internally and externally. This includes data about courses, research outputs, library resources and more. By linking its data to other university and external datasets, the OU aims to create new applications and make existing processes more efficient. Other universities in the UK and worldwide are now following the OU's example in publishing institutional data as linked open data.
A demonstration of the DMPTool, which helps researchers create data management plans now required by the Nat'l Science Foundation and other US grant funding agencies. See http://www.cdlib.org/uc3/webinars/20111019/
for recording.
- The FixRep project aims to examine techniques for automated metadata extraction from documents to enable accessibility evaluation and triage in repositories.
- A prototype was developed to extract formal metadata like file type, title, author from PDFs using tools like pdfinfo, pdftotext, and pdfimages.
- An initial pilot study analyzed PDFs from the University of Bath repository, finding 80% were successfully processed but some errors occurred due to missing or unsupported metadata and formats.
Short talk on Research Object and their use for reproducibility and publishing in the Systems Biology Commons Platform FAIRDOMHub, and the underlying software SEEK.
COMBINE 2019, EU-STANDS4PM, Heidelberg, Germany 18 July 2019
FAIR: Findable Accessable Interoperable Reusable. The “FAIR Principles” for research data, software, computational workflows, scripts, or any other kind of Research Object one can think of, is now a mantra; a method; a meme; a myth; a mystery. FAIR is about supporting and tracking the flow and availability of data across research organisations and the portability and sustainability of processing methods to enable transparent and reproducible results. All this is within the context of a bottom up society of collaborating (or burdened?) scientists, a top down collective of compliance-focused funders and policy makers and an in-the-middle posse of e-infrastructure providers.
Making the FAIR principles a reality is tricky. They are aspirations not standards. They are multi-dimensional and dependent on context such as the sensitivity and availability of the data and methods. We already see a jungle of projects, initiatives and programmes wrestling with the challenges. FAIR efforts have particularly focused on the “last mile” – “FAIRifying” destination community archive repositories and measuring their “compliance” to FAIR metrics (or less controversially “indicators”). But what about FAIR at the first mile, at source and how do we help Alice and Bob with their (secure) data management? If we tackle the FAIR first and last mile, what about the FAIR middle? What about FAIR beyond just data – like exchanging and reusing pipelines for precision medicine?
Since 2008 the FAIRDOM collaboration [1] has worked on FAIR asset management and the development of a FAIR asset Commons for multi-partner researcher projects [2], initially in the Systems Biology field. Since 2016 we have been working with the BioCompute Object Partnership [3] on standardising computational records of HTS precision medicine pipelines.
So, using our FAIRDOM and BioCompute Object binoculars let’s go on a FAIR safari! Let’s peruse the ecosystem, observe the different herds and reflect what where we are for FAIR personalised medicine.
References
[1] http://www.fair-dom.org
[2] http://www.fairdomhub.org
[3] http://www.biocomputeobject.org
JASM2014 talk - "Phinch: An interactive, exploratory data visualization for e...Holly Bik
Phinch is a web-based, interactive data visualization framework for analyzing environmental sequence data and metadata in standard formats like BIOM and tab-delimited files. It allows users to explore patterns in large datasets and export or share visualizations. Future work will add phylogenetic visualizations, more analysis tools, and an open source developer community to expand the framework's capabilities.
Reproducible and citable data and models: an introduction.FAIRDOM
Prepared and presented by Carole Goble (University of Manchester), Wolfgang Mueller (HITS), Dagmar Waltermath (University of Rostock), at the Reproducible and Citable Data and Models Workshop, Warnemünde, Germany. September 14th - 16th 2015.
Semantic Wiki Based Collaborative Scientific Modeling Infrastructure Jie Bao
This document describes a semantic wiki-based collaborative scientific modeling infrastructure that aims to support collaboration, hybrid modeling approaches, and accessibility. It allows users to publish and use scientific data through a wiki interface that integrates semantic technologies to enable formal modeling alongside informal text. The infrastructure provides concept modeling, policy modeling, group information management, and other applications to facilitate scientific collaboration and knowledge management.
Linked Data in a University Context: Publication, Applications and Beyond
The Open University (OU) is exposing its data as linked open data to make it more transparent, reusable and discoverable both internally and externally. This includes data about courses, research outputs, library resources and more. By linking its data to other university and external datasets, the OU aims to create new applications and make existing processes more efficient. Other universities in the UK and worldwide are now following the OU's example in publishing institutional data as linked open data.
A demonstration of the DMPTool, which helps researchers create data management plans now required by the Nat'l Science Foundation and other US grant funding agencies. See http://www.cdlib.org/uc3/webinars/20111019/
for recording.
- The FixRep project aims to examine techniques for automated metadata extraction from documents to enable accessibility evaluation and triage in repositories.
- A prototype was developed to extract formal metadata like file type, title, author from PDFs using tools like pdfinfo, pdftotext, and pdfimages.
- An initial pilot study analyzed PDFs from the University of Bath repository, finding 80% were successfully processed but some errors occurred due to missing or unsupported metadata and formats.
Short talk on Research Object and their use for reproducibility and publishing in the Systems Biology Commons Platform FAIRDOMHub, and the underlying software SEEK.
This presentation presents results from a pilot study exploring automated formal metadata extraction in accessibility evaluation. We demonstrate a prototype created during the FixRep project that aims to support capture, storage and reuse of accessibility information where available, and to approach the problem of reconstructing required data from available sources.
This document discusses challenges with traditional scholarly publishing and opportunities presented by open data and new publishing models.
Traditional publishing incentives prioritize publications over data sharing, which hinders reproducibility and collaboration. This has led to a growing replication gap and increasing retractions. Open data approaches could help by rewarding data release and reuse.
New publishing models are being developed to integrate data, analyses, and publications to better support reproducibility. Initiatives like GigaDB and GigaScience aim to "deconstruct" papers and provide incentives for open peer review, preprints, and implementing analyses in shared platforms like Galaxy. This represents an opportunity to address limitations of traditional publishing.
Scratchpads are virtual research environments that allow taxonomic and biodiversity data to be collected, curated, analyzed, published, and shared in a digital, open, and linked manner. They provide a seamless workflow for data by hosting websites for communities to enter and structure data using standardized modules. This facilitates dissemination of research through open access publishing of datasets, descriptions, keys, and more without reformatting. Major projects like e-Monocot demonstrate Scratchpads' ability to aggregate data from various sources into an integrated portal.
[old] Presentation Of My Projekt Aalborg Fall 2007Charles Seger
This document discusses folksonomies and the challenges of using them to understand user behavior. It presents the speaker's background and research exploring collaborative tagging as part of user information behavior. The speaker seeks to qualitatively investigate user indexing and how registration of tagging results can be combined with a more qualitative approach to better understand user information interaction.
This document summarizes Stephen Abrams' presentation on supporting research data management at the University of California. It discusses the justification for research data management, including funder mandates and evolving scholarly norms. It then describes services provided by the UC Curation Center (UC3) to support research data management at UC campuses, such as the DMPTool for creating data management plans, the Dash data repository, and collaborative projects and initiatives. Challenges in supporting research data management are also noted.
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.
This document summarizes Professor Carole Goble's presentation on making research more reproducible and FAIR (Findable, Accessible, Interoperable, Reusable) through the use of research objects and related standards and infrastructure. It discusses challenges to reproducibility in computational research and proposes bundling datasets, workflows, software and other research products into standardized research objects that can be cited and shared to help address these challenges.
This document discusses the importance of open science and provides recommendations for making research more open, reproducible and accessible. It notes that reproducible research remains a challenge, and that open science has benefits like improving citations, driving further studies, and ensuring ethical and proper use of funds. It recommends using open source software and licenses, uploading datasets and materials to sites like Zenodo for free DOIs, publishing preprints on arXiv, and sharing papers on ResearchGate to promote open access. The overall goal is to make studies fully open through simple and free methods.
Integration of research literature and data (InFoLiS)Philipp Zumstein
Talk at CNI 2015 Spring Membership Meeting in Seattle on April 14th, 2015, see http://www.cni.org/events/membership-meetings/upcoming-meeting/spring-2015/
Abstract: The goal of the InFoLiS project is to connect research data and publications. Links between data and literature are created automatically by means of text mining and made available as Linked Open Data (LOD) for seamless integration into different retrieval systems. This enables scientists to directly access information about corresponding research data in a literature information system, and, vice versa, it is possible to directly find different interpretations and analyses in the literature of the same research data. In our talk, we will describe our methods for generating the links and give insight into the Linked Data infrastructure including the services we are currently building. Most importantly, we will detail how our solutions can be used by other institutions and invite all interested participants to discuss with us their ideas and thoughts on the requirements for these services to ensure broad interoperability with existing systems and infrastructures. InFoLiS is a joint project by the GESIS – Leibniz Institute for the Social Sciences, Cologne, Mannheim University Library, and Mannheim University supported by a grant from the DFG – German Research Foundation.
FAIR data and model management for systems biology.FAIRDOM
Written and presented by Carole Goble (University of Manchester) as part of Intelligent Systems for Molecular Biology (ISMB), Dublin. July 10th - 14th 2015.
DMPTool Webinar Series 1: Introduction to DMPTool Carly Strasser
Slides from DMPTool Webinar Series 1: Introduction to DMPTool, given 28 May 2013. Recording available at http://www.cdlib.org/services/uc3/uc3webinars.html
The document discusses the Names Project, which aims to create a name authority service to help disambiguate author names in digital repositories. It notes the challenges of retrieving materials when an author's name is entered inconsistently. The project works to identify unique individuals, assign them identifiers, and enhance records with information from other sources. It has developed a prototype and is now working to expand it, test matching algorithms, update data mappings, and collaborate with potential users and data providers. An RDF version is also being developed.
The document discusses the future of research communications and some of the drivers shaping it, including technological advances, funding levels, and the needs of the scientific community. It touches on a history of scientific publishing and culture. The core idea is that successful future systems will function as interconnected ecosystems where people, technologies, publications, and data all work together to support argument, evidence, and the scientific social process.
DataCite: the Perfect Complement to CrossRefCrossref
DataCite was created to address the lack of effective ways to link datasets to articles and identify datasets. It assigns digital object identifiers (DOIs) to datasets to allow them to be cited similarly to scholarly articles. Many research institutions and libraries around the world are members of DataCite, including organizations in Europe, North America, and Asia. DataCite helps establish datasets as legitimate contributions to the scientific record that can be identified and cited.
This document summarizes the evolution of biodiversity data systems from desktop-based systems to modern web-based systems. It notes that the amount of biodiversity data has grown exponentially, exceeding Moore's law. It discusses first, second, and third generation data systems and how researchers can choose a system based on their needs and reporting requirements. The document also addresses issues like ensuring data accessibility on the web, dealing with different perspectives on data, and planning for long-term preservation and stability of digital biodiversity data.
The document provides logistics for a webinar on data curation profiles and the DMPTool. It includes instructions for calling into the audio, asking questions in the chat, and finding recordings and slides. The webinar will discuss the history of data curation profiles, comparing them to data management plans, and a case study of using data curation profiles. Data curation profiles involve interviewing researchers about their data practices and needs in order to understand how to support them, while data management plans focus on requirements for funding. Both tools can help librarians engage with researchers, though data curation profiles provide a more in-depth understanding of researchers' full data lifecycles.
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.
The MIAPA ontology: An annotation ontology for validating minimum metadata re...Hilmar Lapp
This document describes the MIAPA (Minimum Information About a Phylogenetic Analysis) ontology, which was developed to standardize the annotation and reporting of metadata for phylogenetic analyses. The MIAPA ontology reuses terms from existing ontologies and is designed according to OBO Foundry best practices. It provides a standard way to annotate key information about phylogenetic tree topologies, operational taxonomic units, branch lengths, character matrices, alignment and tree inference methods. The goal is to facilitate increased access to and reuse of phylogenetic data through consistent annotation of published trees according to the MIAPA standard.
Best Practices for Architecting High Volume, High Performance Publishing for ...Edmunds.com, Inc.
The document discusses best practices for architecting high-volume, high-performance publishing systems for data-intensive websites. It describes using a layered architecture with ActiveMQ for messaging, Camel for routing, and Thrift for data structures and versioning. Techniques covered include virtual topics, throttling, retries, and monitoring to build scalable, fault-tolerant systems that can integrate multiple environments, data centers, applications and data formats.
How Edmunds Got in the Fast Lane: 80% Reduction in Page Load Time in 3 Simple...Edmunds.com, Inc.
The document discusses how Edmunds implemented a JavaScript loader to improve page load times by 80%. It reduced HTTP requests by loading components asynchronously and in parallel after an initial quick page load. Third-party requests were difficult to control, so Edmunds focused on optimizing its own content. The loader declared dependencies, prioritized components, and rendered them sequentially after dependencies were loaded to improve performance while supporting rich content.
This presentation presents results from a pilot study exploring automated formal metadata extraction in accessibility evaluation. We demonstrate a prototype created during the FixRep project that aims to support capture, storage and reuse of accessibility information where available, and to approach the problem of reconstructing required data from available sources.
This document discusses challenges with traditional scholarly publishing and opportunities presented by open data and new publishing models.
Traditional publishing incentives prioritize publications over data sharing, which hinders reproducibility and collaboration. This has led to a growing replication gap and increasing retractions. Open data approaches could help by rewarding data release and reuse.
New publishing models are being developed to integrate data, analyses, and publications to better support reproducibility. Initiatives like GigaDB and GigaScience aim to "deconstruct" papers and provide incentives for open peer review, preprints, and implementing analyses in shared platforms like Galaxy. This represents an opportunity to address limitations of traditional publishing.
Scratchpads are virtual research environments that allow taxonomic and biodiversity data to be collected, curated, analyzed, published, and shared in a digital, open, and linked manner. They provide a seamless workflow for data by hosting websites for communities to enter and structure data using standardized modules. This facilitates dissemination of research through open access publishing of datasets, descriptions, keys, and more without reformatting. Major projects like e-Monocot demonstrate Scratchpads' ability to aggregate data from various sources into an integrated portal.
[old] Presentation Of My Projekt Aalborg Fall 2007Charles Seger
This document discusses folksonomies and the challenges of using them to understand user behavior. It presents the speaker's background and research exploring collaborative tagging as part of user information behavior. The speaker seeks to qualitatively investigate user indexing and how registration of tagging results can be combined with a more qualitative approach to better understand user information interaction.
This document summarizes Stephen Abrams' presentation on supporting research data management at the University of California. It discusses the justification for research data management, including funder mandates and evolving scholarly norms. It then describes services provided by the UC Curation Center (UC3) to support research data management at UC campuses, such as the DMPTool for creating data management plans, the Dash data repository, and collaborative projects and initiatives. Challenges in supporting research data management are also noted.
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.
This document summarizes Professor Carole Goble's presentation on making research more reproducible and FAIR (Findable, Accessible, Interoperable, Reusable) through the use of research objects and related standards and infrastructure. It discusses challenges to reproducibility in computational research and proposes bundling datasets, workflows, software and other research products into standardized research objects that can be cited and shared to help address these challenges.
This document discusses the importance of open science and provides recommendations for making research more open, reproducible and accessible. It notes that reproducible research remains a challenge, and that open science has benefits like improving citations, driving further studies, and ensuring ethical and proper use of funds. It recommends using open source software and licenses, uploading datasets and materials to sites like Zenodo for free DOIs, publishing preprints on arXiv, and sharing papers on ResearchGate to promote open access. The overall goal is to make studies fully open through simple and free methods.
Integration of research literature and data (InFoLiS)Philipp Zumstein
Talk at CNI 2015 Spring Membership Meeting in Seattle on April 14th, 2015, see http://www.cni.org/events/membership-meetings/upcoming-meeting/spring-2015/
Abstract: The goal of the InFoLiS project is to connect research data and publications. Links between data and literature are created automatically by means of text mining and made available as Linked Open Data (LOD) for seamless integration into different retrieval systems. This enables scientists to directly access information about corresponding research data in a literature information system, and, vice versa, it is possible to directly find different interpretations and analyses in the literature of the same research data. In our talk, we will describe our methods for generating the links and give insight into the Linked Data infrastructure including the services we are currently building. Most importantly, we will detail how our solutions can be used by other institutions and invite all interested participants to discuss with us their ideas and thoughts on the requirements for these services to ensure broad interoperability with existing systems and infrastructures. InFoLiS is a joint project by the GESIS – Leibniz Institute for the Social Sciences, Cologne, Mannheim University Library, and Mannheim University supported by a grant from the DFG – German Research Foundation.
FAIR data and model management for systems biology.FAIRDOM
Written and presented by Carole Goble (University of Manchester) as part of Intelligent Systems for Molecular Biology (ISMB), Dublin. July 10th - 14th 2015.
DMPTool Webinar Series 1: Introduction to DMPTool Carly Strasser
Slides from DMPTool Webinar Series 1: Introduction to DMPTool, given 28 May 2013. Recording available at http://www.cdlib.org/services/uc3/uc3webinars.html
The document discusses the Names Project, which aims to create a name authority service to help disambiguate author names in digital repositories. It notes the challenges of retrieving materials when an author's name is entered inconsistently. The project works to identify unique individuals, assign them identifiers, and enhance records with information from other sources. It has developed a prototype and is now working to expand it, test matching algorithms, update data mappings, and collaborate with potential users and data providers. An RDF version is also being developed.
The document discusses the future of research communications and some of the drivers shaping it, including technological advances, funding levels, and the needs of the scientific community. It touches on a history of scientific publishing and culture. The core idea is that successful future systems will function as interconnected ecosystems where people, technologies, publications, and data all work together to support argument, evidence, and the scientific social process.
DataCite: the Perfect Complement to CrossRefCrossref
DataCite was created to address the lack of effective ways to link datasets to articles and identify datasets. It assigns digital object identifiers (DOIs) to datasets to allow them to be cited similarly to scholarly articles. Many research institutions and libraries around the world are members of DataCite, including organizations in Europe, North America, and Asia. DataCite helps establish datasets as legitimate contributions to the scientific record that can be identified and cited.
This document summarizes the evolution of biodiversity data systems from desktop-based systems to modern web-based systems. It notes that the amount of biodiversity data has grown exponentially, exceeding Moore's law. It discusses first, second, and third generation data systems and how researchers can choose a system based on their needs and reporting requirements. The document also addresses issues like ensuring data accessibility on the web, dealing with different perspectives on data, and planning for long-term preservation and stability of digital biodiversity data.
The document provides logistics for a webinar on data curation profiles and the DMPTool. It includes instructions for calling into the audio, asking questions in the chat, and finding recordings and slides. The webinar will discuss the history of data curation profiles, comparing them to data management plans, and a case study of using data curation profiles. Data curation profiles involve interviewing researchers about their data practices and needs in order to understand how to support them, while data management plans focus on requirements for funding. Both tools can help librarians engage with researchers, though data curation profiles provide a more in-depth understanding of researchers' full data lifecycles.
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.
The MIAPA ontology: An annotation ontology for validating minimum metadata re...Hilmar Lapp
This document describes the MIAPA (Minimum Information About a Phylogenetic Analysis) ontology, which was developed to standardize the annotation and reporting of metadata for phylogenetic analyses. The MIAPA ontology reuses terms from existing ontologies and is designed according to OBO Foundry best practices. It provides a standard way to annotate key information about phylogenetic tree topologies, operational taxonomic units, branch lengths, character matrices, alignment and tree inference methods. The goal is to facilitate increased access to and reuse of phylogenetic data through consistent annotation of published trees according to the MIAPA standard.
Best Practices for Architecting High Volume, High Performance Publishing for ...Edmunds.com, Inc.
The document discusses best practices for architecting high-volume, high-performance publishing systems for data-intensive websites. It describes using a layered architecture with ActiveMQ for messaging, Camel for routing, and Thrift for data structures and versioning. Techniques covered include virtual topics, throttling, retries, and monitoring to build scalable, fault-tolerant systems that can integrate multiple environments, data centers, applications and data formats.
How Edmunds Got in the Fast Lane: 80% Reduction in Page Load Time in 3 Simple...Edmunds.com, Inc.
The document discusses how Edmunds implemented a JavaScript loader to improve page load times by 80%. It reduced HTTP requests by loading components asynchronously and in parallel after an initial quick page load. Third-party requests were difficult to control, so Edmunds focused on optimizing its own content. The loader declared dependencies, prioritized components, and rendered them sequentially after dependencies were loaded to improve performance while supporting rich content.
Transforming Edmunds has 500 employees, 18 million monthly visitors, and 30% mobile traffic. Edmunds has used various techniques over the years to transform including Agile in 2007, Design Thinking in 2009, hackathons in 2010, and Continuous Delivery in 2011. Recently, Edmunds has used Design Thinking techniques like personas, prototyping and usability testing to better understand users and design products. Edmunds also holds hackathons to generate new product ideas from its employees and partners. Going forward, Edmunds aims to continue innovating and disrupting itself through experimentation and a focus on understanding user needs.
Comparison of Autotrader, Carfax, Cargurus, Edmunds.com and Other Top Car Buy...Unmetric
This document provides a summary of key metrics and performance for 11 car buying websites on Facebook during Q3 2015. It finds that while CarGurus posted the most content, they received the lowest engagement. CarMax engaged best with fans and saw the highest fan growth. AutoTrader.com had the largest fan base and their posts about a hula doll sweepstakes contest were among their most engaging. In general, the document analyzes and compares engagement, posts, conversations, and other Facebook metrics for the 11 brands over this period.
This document outlines a training program called "Peak Performance for Sales Excellence". The objective of the program is to teach participants how to consistently perform at their highest potential during key sales situations. Over the course of the program, participants will learn about the key elements of peak performance, how to access the proper mindset before important performances, and how to maintain peak performance levels by managing focus and adversity. The program utilizes discussion, case studies, practice sessions, and group work to teach these concepts.
A Guide to SlideShare Analytics - Excerpts from Hubspot's Step by Step Guide ...SlideShare
This document provides a summary of the analytics available through SlideShare for monitoring the performance of presentations. It outlines the key metrics that can be viewed such as total views, actions, and traffic sources over different time periods. The analytics help users identify topics and presentation styles that resonate best with audiences based on view and engagement numbers. They also allow users to calculate important metrics like view-to-contact conversion rates. Regular review of the analytics insights helps users improve future presentations and marketing strategies.
Each month, join us as we highlight and discuss hot topics ranging from the future of higher education to wearable technology, best productivity hacks and secrets to hiring top talent. Upload your SlideShares, and share your expertise with the world!
Not sure what to share on SlideShare?
SlideShares that inform, inspire and educate attract the most views. Beyond that, ideas for what you can upload are limitless. We’ve selected a few popular examples to get your creative juices flowing.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
SlideShare is a global platform for sharing presentations, infographics, videos and documents. It has over 18 million pieces of professional content uploaded by experts like Eric Schmidt and Guy Kawasaki. The document provides tips for setting up an account on SlideShare, uploading content, optimizing it for searchability, and sharing it on social media to build an audience and reputation as a subject matter expert.
Similar to Scott Edmunds & Rob Davidson's talk at the Metabolomics Society 2014 Meeting on Beyond Dead Trees: data & workflow publishing with GigaScience
This document discusses improving reproducibility and transparency in scholarly publishing by rewarding open sharing of data, methods, and results. It presents a case study using the ISA framework to describe experimental data and workflows, nanopublications to make assertions from results, and research objects to aggregate these scholarly artifacts. Combining these approaches could help address issues like increasing retractions by incentivizing open review, replication of analyses, and credit for sharing diverse scholarly contributions beyond publications. The document advocates extending this case study to provide community guidelines for integrated use of these models.
Scott Edmunds slides for class 8 from the HKU Data Curation (module MLIM7350 from the Faculty of Education) course covering science data, medical data and ethics, and the FAIR data principles.
Scott Edmunds flashtalk on "Rewarding Reproducibility and Method Publishing the GigaScience Way" from Beyond the PDF 2 "Making it Happen" session. 20/3/13
This document discusses problems with traditional scholarly publishing and proposes solutions centered around open data and transparency. It notes that traditional publishing hinders reproducibility due to lack of access to data and methods. This has led to an increasing number of non-reproducible findings and retractions. The document advocates for incentivizing the publication of data, software, workflows and other research objects to improve reproducibility and transparency. It highlights several examples where making these elements openly available improved scrutiny and identified errors in published works.
Scott Edmunds talk at AIST: Overcoming the Reproducibility Crisis: and why I ...GigaScience, BGI Hong Kong
This document discusses the growing reproducibility crisis in scientific research and proposes open data and transparent methods as solutions. It notes several studies finding a lack of reproducibility in published research due to inaccessible data and methods. Consequences of this include a large and growing number of retractions as well as perceptions that some regions have higher rates of fraudulent research due to lack of transparency. The document argues that open data, software and peer review can help address these issues by enabling credit for sharing and reusing research objects. Examples of initiatives that aim to reward open practices and improve reproducibility through open data publishing and peer review are also provided.
BioMed Central is a large open access publisher that is committed to open data initiatives. They have implemented several solutions to promote open data practices, including data journals, an open data award, and enabling data citation. They also work to integrate data hosting and deposition, address data licensing issues, and provide guidance on best practices. Future goals include adding more value to text and data mining applications and building business models around open data.
This document summarizes a presentation by Nicole Nogoy from GigaScience about their journal, data platform, and database for large-scale data. GigaScience aims to enable more open access, collaboration and data sharing across disciplines by deconstructing research papers and providing credit for data, software and other digital outputs. It utilizes a big data infrastructure to integrate open access publishing with data and software publishing platforms. Examples are provided of data sets and analyses that have been published through GigaScience to maximize reuse and reproducibility.
Open Research Data: Licensing | Standards | FutureRoss Mounce
This document provides an overview of open research data, including definitions, licensing, standards, and history. It defines open data as data that anyone can freely access, use, modify, and share with few restrictions. For data to be truly open, it recommends using a CC0 public domain waiver or an attribution-only license. It discusses issues with non-commercial and no derivatives restrictions. The document also provides guidance on technical aspects like recommended file formats and standards. It briefly summarizes the history of data sharing, from centralized data centers to online supplementary data to emerging data paper journals. The key messages are that data should be FAIR (Findable, Accessible, Interoperable, Reusable) and that open data benefits both
Scott Edmunds talk at G3 (Great GigaScience & Galaxy) workshop: Open Data: th...GigaScience, BGI Hong Kong
Scott Edmunds talk at G3 (Great GigaScience & Galaxy) workshop: Open Data: the reproducibility crisis, and the need for transparency. Melbourne University 19th September 2014
The document discusses knowledge graphs and their application to scholarly communication. It describes how knowledge graphs can be used to represent scholarly concepts, artifacts, and their relationships in a structured way. This facilitates intuitive exploration and question answering over the represented scholarly content. The document provides examples of how a chemistry experiment could be represented in a knowledge graph and discusses how such representations enable new ways of comparing and surveying research.
A open science presentation focusing on the benefits to be gained and basic practices to follow. This was given on behalf of FOSTER at the Open Science Boos(t)camp event at KU Leuven on 24th October 2014.
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Metadata and Semantics Research Conference, Manchester, UK 2015
Research Objects: why, what and how,
In practice the exchange, reuse and reproduction of scientific experiments is hard, dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: codes fork, data is updated, algorithms are revised, workflows break, service updates are released. Neither should they be viewed just as second-class artifacts tethered to publications, but the focus of research outcomes in their own right: articles clustered around datasets, methods with citation profiles. Many funders and publishers have come to acknowledge this, moving to data sharing policies and provisioning e-infrastructure platforms. Many researchers recognise the importance of working with Research Objects. The term has become widespread. However. What is a Research Object? How do you mint one, exchange one, build a platform to support one, curate one? How do we introduce them in a lightweight way that platform developers can migrate to? What is the practical impact of a Research Object Commons on training, stewardship, scholarship, sharing? How do we address the scholarly and technological debt of making and maintaining Research Objects? Are there any examples
I’ll present our practical experiences of the why, what and how of Research Objects.
Open Research comprises open access to the broad range of research outputs, from journal articles and the underlying data to protocols, results (including negative results), software and tools. Open Research increases inclusivity and collaboration, improves transparency and reproducibility of research and underpins research integrity.
This workshop focuses on the benefits of practicing open research for you as a researcher, to improve discoverability and maximise access to your work and to raise your professional profile.
By the end of the session you will:
• Have an understanding of the principles of Open Research
• Understand open licences and how they apply to publications, data and software
• Be able to apply key tools and techniques to increase the visibility of yourself and your research, including repositories, ORCID, social media and altmetrics
• Describe the different ways of making research and data available open access
Research Object Composer: A Tool for Publishing Complex Data Objects in the C...Anita de Waard
Talk for 2019 research object workflow conference, San Diego, Sept 24, 2019 https://researchobject.github.io/ro2019/
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We present the JWST discovery of SN 2023adsy, a transient object located in a host galaxy JADES-GS
+
53.13485
−
27.82088
with a host spectroscopic redshift of
2.903
±
0.007
. The transient was identified in deep James Webb Space Telescope (JWST)/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Photometric and spectroscopic followup with NIRCam and NIRSpec, respectively, confirm the redshift and yield UV-NIR light-curve, NIR color, and spectroscopic information all consistent with a Type Ia classification. Despite its classification as a likely SN Ia, SN 2023adsy is both fairly red (
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Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...
Scott Edmunds & Rob Davidson's talk at the Metabolomics Society 2014 Meeting on Beyond Dead Trees: data & workflow publishing with GigaScience
1. Beyond Dead Trees: data & workflow
publishing with
Scott Edmunds
Rob Davidson
2. The problems with publishing
• Scholarly articles are merely advertisement of scholarship .
The actual scholarly artefacts, i.e. the data and computational
methods, which support the scholarship, remain largely
inaccessible --- Jon B. Buckheit and David L. Donoho, WaveLab
and reproducible research, 1995
• Lack of transparency, lack of credit for anything other than
“regular” dead tree publication.
• Traditional publishing models, policies and practices holding
things back
3. Why is this important?
…to publish protocols BEFORE analysis
…better access to supporting data/code
…more transparent & accountable review
…to publish replication studies
Need:
4. Consequences: increasing number of retractions
>15X increase in last decade
1. Ioannidis et al., 2009. Repeatability of published microarray gene expression analyses. Nature Genetics 41: 14
2. Science publishing: The trouble with retractions http://www.nature.com/news/2011/111005/full/478026a.html
3. Bjorn Brembs: Open Access and the looming crisis in science https://theconversation.com/open-access-and-the-looming-crisis-in-science-14950
At current % > by 2045 as many papers
published as retracted
5. • Data
• Software
• Review
• Re-use…
= Credit
}
Credit where credit is overdue:
“One option would be to provide researchers who release data to public
repositories with a means of accreditation.”
“An ability to search the literature for all online papers that used a particular data
set would enable appropriate attribution for those who share. “
Nature Biotechnology 27, 579 (2009)
New incentives/credit
6. GigaSolution: deconstructing the paper
www.gigadb.org
www.gigasciencejournal.com
Utilizes big-data infrastructure and expertise from:
Combines and integrates:
Open-access journal
Data Publishing Platform
Data Analysis Platform
9. • Multi Omics focus (not just genomics)
• 10-100x faster download than FTP
• Provide (ISA) curation & integration with other DBs
(e.g. MetaboLights, SRA, etc.)
For more see: http://database.oxfordjournals.org/content/2014/bau018.abstract
11. IRRI GALAXY
Rice 3K project: 3,000 rice genomes, 13.4TB public data
Democratization through data publishing
12. Two tools for reproducible research
Rob Davidson
RO:and
13. GigaSolution: deconstructing the paper
www.gigadb.org
www.gigasciencejournal.com
Utilizes big-data infrastructure and expertise from:
Combines and integrates:
Open-access journal
Data Publishing Platform
Data Analysis Platform
15. Implement workflows in a community-accepted format
http://galaxyproject.org
Over 36,000 main
Galaxy server users
Over 1,000 papers
citing Galaxy use
Over 55 Galaxy
servers deployed
Open source
Rewarding and aiding reproducibility
16. Copyright NBAF-B 2013
Tool Tool parameterisation Results panel
Rewarding and aiding reproducibility
Implement workflows in a community-accepted format
22. Aiding reproducibility
OMERO: providing
access to imaging data
View, filter, measure raw
images with direct links
from journal article.
See all image data, not
just cherry picked
examples.
Download and reprocess.
25. In Summary
• Reproducibility is important!!
– Currently not very common!
• Many tools appearing for data publishing and
sharing (images, tools, workflows).
• Data publishing → more publications, more
citations, more impact!
• Are you convinced?
• What barriers? Code standards? Data
standards? Too much work?
26. Give us data, papers &
pipelines*
Help us make it
happen!
scott@gigasciencejournal.com
rob@gigasciencejournal.com
editorial@gigasciencejournal.com
database@gigasciencejournal.com
Contact us:
* APC’s currently generously covered
by BGI until 2015
www.gigasciencejournal.com
27. Ruibang Luo (BGI/HKU)
Shaoguang Liang (BGI-SZ)
Tin-Lap Lee (CUHK)
Qiong Luo (HKUST)
Senghong Wang (HKUST)
Yan Zhou (HKUST)
Thanks to:
@gigascience
facebook.com/GigaScience
blogs.biomedcentral.com/gigablog/
Peter Li
Huayan Gao
Chris Hunter
Jesse Si Zhe
Nicole Nogoy
Laurie Goodman
Amye Kenall (BMC)
Marco Roos (LUMC)
Mark Thompson (LUMC)
Jun Zhao (Lancaster)
Susanna Sansone (Oxford)
Philippe Rocca-Serra (Oxford)
Alejandra Gonzalez-Beltran (Oxford)
www.gigadb.org
galaxy.cbiit.cuhk.edu.hk
www.gigasciencejournal.com
CBIITFunding from:
Our collaborators:team:
Editor's Notes
Over 20,000 users on the main server
Over 500 papers citing the use of Galaxy
Over 55 servers deployed on the Web
That just leaves me to thank the GigaScience team: Laurie, Scott, Alexandra, Peter and Jesse, BGI for their support - specifically Shaoguang for IT and bioinformatics support – our collaborators on the database, website and tools: Tin-Lap, Qiong, Senhong, Yan, the Cogini web design team, Datacite for providing the DOI service and the isacommons team for their support and advocacy for best practice use of metadata reporting and sharing.
Thank you for listening.