We built a semantic web image repository called FlyTED to publish Drosophila gene expression images online and make them searchable. We used existing tools like Eprints to store metadata and images and made the metadata accessible through SPARQL. We then consumed the images and metadata in faceted browsers like Exhibit and jSpace to present them in more flexible user interfaces. This allows components like the metadata storage to potentially be replaced in the future with new tools.
Presentation on the Resource Identification Pilot Project, an initiative to develop a machine-processable citation system for key research resources used in scientific studies
Presentation on the Resource Identification Pilot Project, an initiative to develop a machine-processable citation system for key research resources used in scientific studies
Metagenomic Data Provenance and Management using the ISA infrastructure --- o...Alejandra Gonzalez-Beltran
Metagenomic Data Provenance and Management using the ISA infrastructure - overview, implementation patterns & software tools
Slides presented at EBI Metagenomics Bioinformatics course: http://www.ebi.ac.uk/training/course/metagenomics2014
Standard Provenance Reporting and Scientific Software Management in Virtual L...njcar
The Virtual Hazards Impact & Risk Laboratory (VHIRL) is a scientific workflow portal that provides researchers with access to a cloud computing environment for natural hazards eResearch tools. It allows researchers to construct experiments with data from a variety of sources and execute cloud computing processes for rapid and remote simulation and analysis. The service currently includes tools for the simulation of three major hazards affecting the Asia-Pacific region: earthquakes, tsunamis and tropical cyclones.
For scientific results, the establishment of provenance is key to reproducibility and trust. Thus the need for any virtual laboratory to provide provenance information for the tasks it manages is obvious, but the appropriate way to report and manage provenance information is not always so straightforward. Many virtual laboratories and workflow systems provide bespoke provenance management with a focus on internal system use. This has clear benefits for reproducibility within the system, but it limits the interoperability of systems. For VHIRL, a provenance solution was required that was as
interoperable with other, external, provenance systems as possible.
A related common issue facing workflow tools and virtual laboratories is the need to manage software code. With this comes well-known issues associated with code sharing: licensing, source code management, version management and dependency resolution. There are a wide selection of commonly used tools to help solve these problems, for example Git and Subversion.
A key goal of VHIRL was to externalise as much information management as was reasonable. VHIRL is a virtual laboratory: it is not designed to be a data store, software repository, or records management system. A solution was required that could hand off the management of provenance records and code to external services, with links between them, other data services and VHIRL jobs where appropriate.
Scientific software can be quite complicated and systems for managing dependencies and source vary from system to system. In order to provide the least friction for authors of software, we designed a system called the Scientific Software Solution Centre (SSSC) to manage solutions to scientific problems and deliver the solution templates, code and dependencies that enable them for use in VHIRL and other Virtual Laboratories and applications.
Executing Provenance-Enabled Queries over Web DataeXascale Infolab
The proliferation of heterogeneous Linked Data on the Web poses new challenges to database systems. In particular, because of this heterogeneity, the capacity to store, track, and query provenance data is becoming a pivotal feature of modern triple stores. In this paper, we tackle the problem of efficiently executing provenance-enabled queries over RDF data. We propose, implement and empirically evaluate five different query execution strategies for RDF queries that incorporate knowledge of provenance. The evaluation is conducted on Web Data obtained from two different Web crawls (The Billion Triple Challenge, and the Web Data Commons). Our evaluation shows that using an adaptive query materialization execution strategy performs best in our context. Interestingly, we find that because provenance is prevalent within Web Data and is highly selective, it can be used to improve query processing performance. This is a counterintuitive result as provenance is often associated with additional overhead.
ACS 248th Paper 146 VIVO/ScientistsDB Integration into EurekaStuart Chalk
Development of plugins for access to researchers identified in VIVO on the ScientistsDB website. Also developed a plugin to access Elasticsearch from within Eureka.
247th ACS Meeting: The Eureka Research WorkbenchStuart Chalk
Academic scientists need a tool to capture the science they do so that it can be shared in open science, integrated with linked data, and shared/searched. Eureka is an evolving platform to do this.
ACS 248th Paper 136 JSmol/JSpecView Eureka IntegrationStuart Chalk
Integration of the combined JSmol/JSpecView molecular viewer/spectral viewer software in the Eureka Research Workbench. Can display molecular structures, spectra and the linked version where clicking on a peak shows molecular movement (IR).
Presentation on the use of the Eureka Research Workbench to store data and scientific workflow information. Presented online as part of the Dial-a-molecule 'Liberating Laboratory Data' event (http://www.dial-a-molecule.org/wp/events-listing/liberating-laboratory-data/)
Eureka Research Workbench: A Semantic Approach to an Open Source Electroni...Stuart Chalk
Scientists are looking for ways to leverage web 2.0 technologies in the research laboratory and as a consequence a number of approaches to web-based electronic notebooks are being evaluated. In this presentation I discuss the Eureka Research Workbench, an electronic laboratory notebook built on semantic technology and XML. Using this approach the context of the information recorded in the laboratory can be captured and searched along with the data itself. A discussion of the current system is presented along with the next planned development of the framework and long-term plans relative to linked open data. Presented at the 246th American Chemical Society Meeting in Indianapolis, IN, USA on September 12th, 2013.
ImageJ2 is a new version of ImageJ for the next generation of multidimensional image data, with a focus on scientific imaging. Its central goal is to broaden the paradigm of ImageJ beyond the limitations of ImageJ 1.x, to support the next generation of multidimensional scientific imaging.
ImageJ2 is more than just an application: it is also a collection of reusable software libraries built on the SciJava software stack, using a powerful plugin framework to facilitate rapid development and painless user customization.
This talk provides an overview of the motivation behind the ImageJ2 project and related SciJava software projects, and quickly covers some of ImageJ2's current features.
ImageSnippets - Using Linked Data Metadata to Organize, Share and Publish you...Margaret Warren
ImageSnippets is a general purpose product for managing your images that uses linked data metadata for image description. Keywords become more meaningful, searching for images is enriched. More accurate descriptions can be gathered by experts across your global teams. Images can be published with your publishing intentions remaining clearly associated with your images.
RO-Crate: packaging metadata love notes into FAIR Digital ObjectsCarole Goble
Abstract
slides available at: https://zenodo.org/record/7147703#.Y7agoxXP2F4
The Helmholtz Metadata Collaboration aims to make the research data [and software] produced by Helmholtz Centres FAIR for their own and the wider science community by means of metadata enrichment [1]. Why metadata enrichment and why FAIR? Because the whole scientific enterprise depends on a cycle of finding, exchanging, understanding, validating, reproducing), integrating and reusing research entities across a dispersed community of researchers.
Metadata is not just “a love note to the future” [2], it is a love note to today’s collaborators and peers. Moreover, a FAIR Commons must cater for the metadata of all the entities of research – data, software, workflows, protocols, instruments, geo-spatial locations, specimens, samples, people (well as traditional articles) – and their interconnectivity. That is a lot of metadata love notes to manage, bundle up and move around. Notes written in different languages at different times by different folks, produced and hosted by different platforms, yet referring to each other, and building an integrated picture of a multi-part and multi-party investigation. We need a crate!
RO-Crate [3] is an open, community-driven, and lightweight approach to packaging research entities along with their metadata in a machine-readable manner. Following key principles - “just enough” and “developer and legacy friendliness - RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility and citability. As a self-describing and unbounded “metadata middleware” framework RO-Crate shows that a little bit of packaging goes a long way to realise the goals of FAIR Digital Objects (FDO)[4], and to not just overcome platform diversity but celebrate it while retaining investigation contextual integrity.
In this talk I will present the why, and how Research Object packaging eases Metadata Collaboration using examples in big data and mixed object exchange, mixed object archiving and publishing, mass citation, and reproducibility. Some examples come from the HMC, others from EOSC, USA and Australia, and from different disciplines.
Metadata is a love note to the future, RO-Crate is the delivery package.
[1] https://helmholtz-metadaten.de/en
[2] Scott, Jason The Metadata Mania, http://ascii.textfiles.com/archives/3181, June 2011
[3] Soiland-Reyes, Stian et al. “Packaging Research Artefacts with RO-Crate”. Data Science, 2022; 5(2):97-138, DOI: 10.3233/DS-210053
[4] De Smedt K, Koureas D, Wittenburg P. “FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units”. Publications. 2020; 8(2):21. https://doi.org/10.3390/publications8020021
Metagenomic Data Provenance and Management using the ISA infrastructure --- o...Alejandra Gonzalez-Beltran
Metagenomic Data Provenance and Management using the ISA infrastructure - overview, implementation patterns & software tools
Slides presented at EBI Metagenomics Bioinformatics course: http://www.ebi.ac.uk/training/course/metagenomics2014
Standard Provenance Reporting and Scientific Software Management in Virtual L...njcar
The Virtual Hazards Impact & Risk Laboratory (VHIRL) is a scientific workflow portal that provides researchers with access to a cloud computing environment for natural hazards eResearch tools. It allows researchers to construct experiments with data from a variety of sources and execute cloud computing processes for rapid and remote simulation and analysis. The service currently includes tools for the simulation of three major hazards affecting the Asia-Pacific region: earthquakes, tsunamis and tropical cyclones.
For scientific results, the establishment of provenance is key to reproducibility and trust. Thus the need for any virtual laboratory to provide provenance information for the tasks it manages is obvious, but the appropriate way to report and manage provenance information is not always so straightforward. Many virtual laboratories and workflow systems provide bespoke provenance management with a focus on internal system use. This has clear benefits for reproducibility within the system, but it limits the interoperability of systems. For VHIRL, a provenance solution was required that was as
interoperable with other, external, provenance systems as possible.
A related common issue facing workflow tools and virtual laboratories is the need to manage software code. With this comes well-known issues associated with code sharing: licensing, source code management, version management and dependency resolution. There are a wide selection of commonly used tools to help solve these problems, for example Git and Subversion.
A key goal of VHIRL was to externalise as much information management as was reasonable. VHIRL is a virtual laboratory: it is not designed to be a data store, software repository, or records management system. A solution was required that could hand off the management of provenance records and code to external services, with links between them, other data services and VHIRL jobs where appropriate.
Scientific software can be quite complicated and systems for managing dependencies and source vary from system to system. In order to provide the least friction for authors of software, we designed a system called the Scientific Software Solution Centre (SSSC) to manage solutions to scientific problems and deliver the solution templates, code and dependencies that enable them for use in VHIRL and other Virtual Laboratories and applications.
Executing Provenance-Enabled Queries over Web DataeXascale Infolab
The proliferation of heterogeneous Linked Data on the Web poses new challenges to database systems. In particular, because of this heterogeneity, the capacity to store, track, and query provenance data is becoming a pivotal feature of modern triple stores. In this paper, we tackle the problem of efficiently executing provenance-enabled queries over RDF data. We propose, implement and empirically evaluate five different query execution strategies for RDF queries that incorporate knowledge of provenance. The evaluation is conducted on Web Data obtained from two different Web crawls (The Billion Triple Challenge, and the Web Data Commons). Our evaluation shows that using an adaptive query materialization execution strategy performs best in our context. Interestingly, we find that because provenance is prevalent within Web Data and is highly selective, it can be used to improve query processing performance. This is a counterintuitive result as provenance is often associated with additional overhead.
ACS 248th Paper 146 VIVO/ScientistsDB Integration into EurekaStuart Chalk
Development of plugins for access to researchers identified in VIVO on the ScientistsDB website. Also developed a plugin to access Elasticsearch from within Eureka.
247th ACS Meeting: The Eureka Research WorkbenchStuart Chalk
Academic scientists need a tool to capture the science they do so that it can be shared in open science, integrated with linked data, and shared/searched. Eureka is an evolving platform to do this.
ACS 248th Paper 136 JSmol/JSpecView Eureka IntegrationStuart Chalk
Integration of the combined JSmol/JSpecView molecular viewer/spectral viewer software in the Eureka Research Workbench. Can display molecular structures, spectra and the linked version where clicking on a peak shows molecular movement (IR).
Presentation on the use of the Eureka Research Workbench to store data and scientific workflow information. Presented online as part of the Dial-a-molecule 'Liberating Laboratory Data' event (http://www.dial-a-molecule.org/wp/events-listing/liberating-laboratory-data/)
Eureka Research Workbench: A Semantic Approach to an Open Source Electroni...Stuart Chalk
Scientists are looking for ways to leverage web 2.0 technologies in the research laboratory and as a consequence a number of approaches to web-based electronic notebooks are being evaluated. In this presentation I discuss the Eureka Research Workbench, an electronic laboratory notebook built on semantic technology and XML. Using this approach the context of the information recorded in the laboratory can be captured and searched along with the data itself. A discussion of the current system is presented along with the next planned development of the framework and long-term plans relative to linked open data. Presented at the 246th American Chemical Society Meeting in Indianapolis, IN, USA on September 12th, 2013.
ImageJ2 is a new version of ImageJ for the next generation of multidimensional image data, with a focus on scientific imaging. Its central goal is to broaden the paradigm of ImageJ beyond the limitations of ImageJ 1.x, to support the next generation of multidimensional scientific imaging.
ImageJ2 is more than just an application: it is also a collection of reusable software libraries built on the SciJava software stack, using a powerful plugin framework to facilitate rapid development and painless user customization.
This talk provides an overview of the motivation behind the ImageJ2 project and related SciJava software projects, and quickly covers some of ImageJ2's current features.
ImageSnippets - Using Linked Data Metadata to Organize, Share and Publish you...Margaret Warren
ImageSnippets is a general purpose product for managing your images that uses linked data metadata for image description. Keywords become more meaningful, searching for images is enriched. More accurate descriptions can be gathered by experts across your global teams. Images can be published with your publishing intentions remaining clearly associated with your images.
RO-Crate: packaging metadata love notes into FAIR Digital ObjectsCarole Goble
Abstract
slides available at: https://zenodo.org/record/7147703#.Y7agoxXP2F4
The Helmholtz Metadata Collaboration aims to make the research data [and software] produced by Helmholtz Centres FAIR for their own and the wider science community by means of metadata enrichment [1]. Why metadata enrichment and why FAIR? Because the whole scientific enterprise depends on a cycle of finding, exchanging, understanding, validating, reproducing), integrating and reusing research entities across a dispersed community of researchers.
Metadata is not just “a love note to the future” [2], it is a love note to today’s collaborators and peers. Moreover, a FAIR Commons must cater for the metadata of all the entities of research – data, software, workflows, protocols, instruments, geo-spatial locations, specimens, samples, people (well as traditional articles) – and their interconnectivity. That is a lot of metadata love notes to manage, bundle up and move around. Notes written in different languages at different times by different folks, produced and hosted by different platforms, yet referring to each other, and building an integrated picture of a multi-part and multi-party investigation. We need a crate!
RO-Crate [3] is an open, community-driven, and lightweight approach to packaging research entities along with their metadata in a machine-readable manner. Following key principles - “just enough” and “developer and legacy friendliness - RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility and citability. As a self-describing and unbounded “metadata middleware” framework RO-Crate shows that a little bit of packaging goes a long way to realise the goals of FAIR Digital Objects (FDO)[4], and to not just overcome platform diversity but celebrate it while retaining investigation contextual integrity.
In this talk I will present the why, and how Research Object packaging eases Metadata Collaboration using examples in big data and mixed object exchange, mixed object archiving and publishing, mass citation, and reproducibility. Some examples come from the HMC, others from EOSC, USA and Australia, and from different disciplines.
Metadata is a love note to the future, RO-Crate is the delivery package.
[1] https://helmholtz-metadaten.de/en
[2] Scott, Jason The Metadata Mania, http://ascii.textfiles.com/archives/3181, June 2011
[3] Soiland-Reyes, Stian et al. “Packaging Research Artefacts with RO-Crate”. Data Science, 2022; 5(2):97-138, DOI: 10.3233/DS-210053
[4] De Smedt K, Koureas D, Wittenburg P. “FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units”. Publications. 2020; 8(2):21. https://doi.org/10.3390/publications8020021
This talk explores how principles derived from experimental design practice, data and computational models can greatly enhance data quality, data generation, data reporting, data publication and data review.
FAIR Workflows and Research Objects get a Workout Carole Goble
So, you want to build a pan-national digital space for bioscience data and methods? That works with a bunch of pre-existing data repositories and processing platforms? So you can share FAIR workflows and move them between services? Package them up with data and other stuff (or just package up data for that matter)? How? WorkflowHub (https://workflowhub.eu) and RO-Crate Research Objects (https://www.researchobject.org/ro-crate) that’s how! A step towards FAIR Digital Objects gets a workout.
Presented at DataVerse Community Meeting 2021
Center for Open Science and the Open Science Framework: Dataverse Add-on by S...datascienceiqss
The Open Science Framework (OSF: http://osf.io; supported and maintained by the Center for Open Science - COS: http://centerforopenscience.org/) is a free, open source workflow management service and repository designed for scientists to manage and connect everything across their research process. One of the first add-on connections was Dataverse, which provides value to users through an easy connection as a repository service. This talk will introduce the Dataverse add-on connection and provide a technical view of how it was built and how it connects the OSF and Dataverse.
Rule-based Capture/Storage of Scientific Data from PDF Files and Export using...Stuart Chalk
Recently, the US government has mandated that publicly funded scientific research data be freely made available in a useable form, allowing integration of data in other systems. While this mandate has been articulated, existing publications and new papers (PDF) still do not provide accessible data, meaning that the usefulness is limited without human intervention.
This presentation outlines our efforts to extract scientific data from PDF files, using the PDFToText software and regular expressions (regex), and process it into a form that structures the data and its context (metadata). Extracted data is processed (cleaned, normalized), organized, and inserted into a contextually developed MySQL database. The data and metadata can then be output using a generic JSON-LD based scientific data model (SDM) under development in our laboratory.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
2008 Jun Zhao Eswc
1. Building a Semantic Web Image Repository for Biological Research Images Jun Zhao , Graham Klyne and David Shotton [email_address] Image Bioinformatics Research Group Department of Zoology University of Oxford, UK
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![Building a Semantic Web Image Repository for Biological Research Images Jun Zhao , Graham Klyne and David Shotton [email_address] Image Bioinformatics Research Group Department of Zoology University of Oxford, UK](https://image.slidesharecdn.com/2008junzhaoeswc-1213209032733549-8/85/2008-Jun-Zhao-Eswc-1-320.jpg)
![FlyTED ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)