Using electronic laboratory notebooks in the academic life sciences: a group ...SC CTSI at USC and CHLA
This document summarizes a webinar on using electronic laboratory notebooks (eLNs). The webinar featured a presentation by Dr. Ulrich Dirnagl on his experience using eLNs to make research teams more efficient. He believes paper notebooks are outdated and that eLNs can help address the reproducibility crisis in research. The webinar covered the benefits of eLNs like collaboration, data sharing, and compliance with regulations. It also reviewed different types of eLNs and pricing models. While implementation challenges exist, eLNs were found to improve oversight, record keeping, and transparency if selected and supported properly.
Scientific Software: Sustainability, Skills & SociologyNeil Chue Hong
This document discusses the importance of software sustainability. It notes that software is everywhere, long-lived, and hard to define, which makes sustainability challenging. It emphasizes that software sustainability requires cultivating skills in developers and researchers, providing proper incentives, and recognizing that people are a key part of maintaining software over long periods of time.
Keynote presentation at IEEE TALE 2013 conference - A Second Step Ahead in the Future of Labs and Learning: MOOCs, Widgets, Ubiquity and Mobility - Bali, Indonesia, August 2013 http://www.tale-conference.org/tale2013/
The Bioinformatic, Intelligent Systems and Educational Technology (BISITE) group brings Together a group of researchers interested primarily in the development and application of intelligent computer systems to various types of problems.
This document outlines a sustainability plan for the SpeakApps project with four key areas: tools and platform, business model, community, and pedagogical development. It identifies sub-components that need to be addressed for each area, including maintaining and upgrading the tools, integrating with learning platforms, determining responsibility for ongoing maintenance, and developing a business model. Action items are noted for various project partners to contribute to discussions on these topics to help ensure the long-term sustainability of the SpeakApps tools and resources.
The Assistive Technology Group at Politecnico di Milano identifies, forecasts, implements, promotes and applies innovative ICT methods and technologies to develop sustainable solutions for vulnerable groups. The group's mission is to guarantee recovery of functionality, social integration, equal opportunities, health, self-determination and quality of life. Key areas of research include building automation, auxiliary supports like brain-computer interfaces, pattern recognition, innovations in areas like chemical education and campus accessibility, and natural language processing projects. The group collaborates with enterprises, public institutions, and other organizations and universities on various projects.
The document discusses technology-enhanced learning and accessibility, outlining three key dimensions: the learner dimension which models individual learner preferences, the content dimension for creating accessible learning objects and tagging them with metadata, and tools/applications. It also introduces the e-Access2Learn framework for empowering stakeholders in technology-enhanced learning through universally accessible systems.
Using electronic laboratory notebooks in the academic life sciences: a group ...SC CTSI at USC and CHLA
This document summarizes a webinar on using electronic laboratory notebooks (eLNs). The webinar featured a presentation by Dr. Ulrich Dirnagl on his experience using eLNs to make research teams more efficient. He believes paper notebooks are outdated and that eLNs can help address the reproducibility crisis in research. The webinar covered the benefits of eLNs like collaboration, data sharing, and compliance with regulations. It also reviewed different types of eLNs and pricing models. While implementation challenges exist, eLNs were found to improve oversight, record keeping, and transparency if selected and supported properly.
Scientific Software: Sustainability, Skills & SociologyNeil Chue Hong
This document discusses the importance of software sustainability. It notes that software is everywhere, long-lived, and hard to define, which makes sustainability challenging. It emphasizes that software sustainability requires cultivating skills in developers and researchers, providing proper incentives, and recognizing that people are a key part of maintaining software over long periods of time.
Keynote presentation at IEEE TALE 2013 conference - A Second Step Ahead in the Future of Labs and Learning: MOOCs, Widgets, Ubiquity and Mobility - Bali, Indonesia, August 2013 http://www.tale-conference.org/tale2013/
The Bioinformatic, Intelligent Systems and Educational Technology (BISITE) group brings Together a group of researchers interested primarily in the development and application of intelligent computer systems to various types of problems.
This document outlines a sustainability plan for the SpeakApps project with four key areas: tools and platform, business model, community, and pedagogical development. It identifies sub-components that need to be addressed for each area, including maintaining and upgrading the tools, integrating with learning platforms, determining responsibility for ongoing maintenance, and developing a business model. Action items are noted for various project partners to contribute to discussions on these topics to help ensure the long-term sustainability of the SpeakApps tools and resources.
The Assistive Technology Group at Politecnico di Milano identifies, forecasts, implements, promotes and applies innovative ICT methods and technologies to develop sustainable solutions for vulnerable groups. The group's mission is to guarantee recovery of functionality, social integration, equal opportunities, health, self-determination and quality of life. Key areas of research include building automation, auxiliary supports like brain-computer interfaces, pattern recognition, innovations in areas like chemical education and campus accessibility, and natural language processing projects. The group collaborates with enterprises, public institutions, and other organizations and universities on various projects.
The document discusses technology-enhanced learning and accessibility, outlining three key dimensions: the learner dimension which models individual learner preferences, the content dimension for creating accessible learning objects and tagging them with metadata, and tools/applications. It also introduces the e-Access2Learn framework for empowering stakeholders in technology-enhanced learning through universally accessible systems.
An Open and Improved VISIR System Through PILAR Federation for Electrical/Ele...Manuel Castro
Worksho of PILAR Federated VISIR systems celebrated in the TALE 2018 conference (Teaching, Assessment and Learning for Engineering) in December 2018, in Wollongong (Australia). Here you have the PILAR project link >>> http://www.ieec.uned.es/pilar-project/index.html?lng=en
Standardization of Online Laboratories for Education. 2015-11-19eMadrid network
The document discusses work in progress on standardizing online laboratories for education. It describes the scope and content of the proposed standard, including definitions of key terms like online laboratory, remote laboratory, and virtual laboratory. It outlines different standardization levels from embedded things to embedded pedagogy. It provides overviews of the draft standard sections on normative references, definitions, the laboratory as a service and laboratory as an open educational resource. The document also discusses metadata, learner experience, and learning outcomes including the use of xAPI statements to track learner activities in an online laboratory.
Work in Progress on the Standardization of Online Laboratories for EducationMiguel R. Artacho
In the last years we have witness the increasing use of remote laboratories in education, encompassed by the development of technology enhanced learning from k-12 to higher education. In this context there is a need, on one hand to define and establish a common consensus on the structure and operation of remote laboratories (RL) from learning technologies perspective as open educational resources (OER) independent from LMSs. On the other hand, cloud computing and the concept of XaaS makes meaningful to consider laboratories as another lego piece of an educational resource in the cloud with a focus on potential standardardized information models and protocols as a common basis for instructional interoperability based on search, retrieval, labeling and services for educational purposes.
This document summarizes a presentation given by Denis Gillet and Christophe Salzmann from EPFL on remote labs 2.0 using social media and smart devices. It discusses EPFL's experience with remote labs since 1992, including the transition to web-based experiments accessible over the internet. It proposes developing remote labs as smart devices that can be integrated into social media platforms and accessed from a variety of devices. This would simplify development and allow experiments to be customized, shared and reused more easily across different contexts.
This document introduces FAIRDOM, a consortium that provides a platform and services to help researchers organize, manage, share, and preserve research outputs according to FAIR principles. FAIRDOM has been in operation for 10 years and has over 50 installations supporting over 118 projects. It provides tools and services to help researchers collaborate better and integrate their data, models, publications and other research objects. FAIRDOM also works with other organizations and infrastructure providers to support broader research initiatives.
The document outlines the vision, mission, and strategy of the STFC (Science and Technology Facilities Council) in implementing e-Science technologies. The goals are to exploit data from STFC facilities through innovative infrastructure, integrate activities nationally and internationally, and improve computation and data management capabilities to enable new scientific discoveries.
Keynote on software sustainability given at the 2nd Annual Netherlands eScience Symposium, November 2014.
Based on the article
Carole Goble ,
Better Software, Better Research
Issue No.05 - Sept.-Oct. (2014 vol.18)
pp: 4-8
IEEE Computer Society
http://www.computer.org/csdl/mags/ic/2014/05/mic2014050004.pdf
http://doi.ieeecomputersociety.org/10.1109/MIC.2014.88
http://www.software.ac.uk/resources/publications/better-software-better-research
The document discusses the creation of a wiki catalogue to catalog open source toolkits and testbeds related to software defined networking (SDN), network function virtualization (NFV), mobile edge computing (MEC) and 5G technologies. It notes that there are many toolkits and testbeds but a lack of visibility among researchers. A wiki is proposed to provide a centralized place for researchers, students and developers to discover relevant tools and testbeds. The wiki is being developed in phases, beginning with data collection and developing the initial structure, then opening it for community contributions and updates.
Presentation on "Practical Competences in Engineering and Technology Enhanced Learning: MOOCs and Emerging Areas at the IEEE Education Society" from the IEEE Education Society Special Technical Community on Learning Sciences at the The Chinese University of Hong Kong
Presentation of the paper Creating a distributed mobile networking testbed environment - through the Living Labs approach, Proceedings of 2nd International IEEE/Create-Net Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TridentCom), Barcelona, Spain, March, 2006.
PROnet is an NSF-supported research project being conducted by researchers at the University of Texas at Dallas. PROnet is dedicated to enabling the design, development, demonstration and deployment of innovative ultrahigh-speed low-latency applications being created in and across North Texas and beyond.
Analyzing Big Data in Medicine with Virtual Research Environments and Microse...Ola Spjuth
This document discusses analyzing big data in medicine using virtual research environments and microservices. It notes the vast amount of data being generated and challenges of data management, analysis and scaling. The European Open Science Cloud aims to enable access to shared scientific data across borders. Contemporary analysis uses high-performance computing but has limitations. Cloud computing, virtual machines, containers and microservices can help address these challenges by providing on-demand resources and decomposing functionality into independent services. The PhenoMeNal project is building a standardized e-infrastructure using these approaches to enable users to access tools and data. This improves sustainability, reliability, scalability and enables agile development and science.
Widget and Smart Devices. A Different Approach for Remote and Virtual labsUNED
A vast number of learning content and tools can be found over Internet. Currently, most of them are ad-hoc solutions which are developed for a particular learning platform or environment. New concepts, such as Widgets, Smart devices, Internet of Thing and learning Clouds, are ideas whose goals is the creation of shareable online learning scenarios over different devices and environments.
German Conference on Bioinformatics 2021
https://gcb2021.de/
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
Elsevier‘s RDM Program: Habits of Effective Data and the Bourne UlitmatumAnita de Waard
Elsevier's RDM Program: Ten Habits of Highly Effective Data
The document outlines Elsevier's research data management (RDM) program and efforts to support the effective management of research data. It discusses a "Maslow hierarchy" with 10 aspects of highly effective research data from stored to integrated. It provides examples of Elsevier's RDM tools and services like Hivebench, Mendeley Data, and DataSearch that help support storing, sharing, citing, and discovering research data. It also discusses collaborative RDM efforts like Force11, Research Data Alliance, and Crossref as well as journal initiatives to improve reproducibility. The document concludes with a proposed partnership where an institution could pilot and provide feedback on Elsevier's
An Open and Improved VISIR System Through PILAR Federation for Electrical/Ele...Manuel Castro
Worksho of PILAR Federated VISIR systems celebrated in the TALE 2018 conference (Teaching, Assessment and Learning for Engineering) in December 2018, in Wollongong (Australia). Here you have the PILAR project link >>> http://www.ieec.uned.es/pilar-project/index.html?lng=en
Standardization of Online Laboratories for Education. 2015-11-19eMadrid network
The document discusses work in progress on standardizing online laboratories for education. It describes the scope and content of the proposed standard, including definitions of key terms like online laboratory, remote laboratory, and virtual laboratory. It outlines different standardization levels from embedded things to embedded pedagogy. It provides overviews of the draft standard sections on normative references, definitions, the laboratory as a service and laboratory as an open educational resource. The document also discusses metadata, learner experience, and learning outcomes including the use of xAPI statements to track learner activities in an online laboratory.
Work in Progress on the Standardization of Online Laboratories for EducationMiguel R. Artacho
In the last years we have witness the increasing use of remote laboratories in education, encompassed by the development of technology enhanced learning from k-12 to higher education. In this context there is a need, on one hand to define and establish a common consensus on the structure and operation of remote laboratories (RL) from learning technologies perspective as open educational resources (OER) independent from LMSs. On the other hand, cloud computing and the concept of XaaS makes meaningful to consider laboratories as another lego piece of an educational resource in the cloud with a focus on potential standardardized information models and protocols as a common basis for instructional interoperability based on search, retrieval, labeling and services for educational purposes.
This document summarizes a presentation given by Denis Gillet and Christophe Salzmann from EPFL on remote labs 2.0 using social media and smart devices. It discusses EPFL's experience with remote labs since 1992, including the transition to web-based experiments accessible over the internet. It proposes developing remote labs as smart devices that can be integrated into social media platforms and accessed from a variety of devices. This would simplify development and allow experiments to be customized, shared and reused more easily across different contexts.
This document introduces FAIRDOM, a consortium that provides a platform and services to help researchers organize, manage, share, and preserve research outputs according to FAIR principles. FAIRDOM has been in operation for 10 years and has over 50 installations supporting over 118 projects. It provides tools and services to help researchers collaborate better and integrate their data, models, publications and other research objects. FAIRDOM also works with other organizations and infrastructure providers to support broader research initiatives.
The document outlines the vision, mission, and strategy of the STFC (Science and Technology Facilities Council) in implementing e-Science technologies. The goals are to exploit data from STFC facilities through innovative infrastructure, integrate activities nationally and internationally, and improve computation and data management capabilities to enable new scientific discoveries.
Keynote on software sustainability given at the 2nd Annual Netherlands eScience Symposium, November 2014.
Based on the article
Carole Goble ,
Better Software, Better Research
Issue No.05 - Sept.-Oct. (2014 vol.18)
pp: 4-8
IEEE Computer Society
http://www.computer.org/csdl/mags/ic/2014/05/mic2014050004.pdf
http://doi.ieeecomputersociety.org/10.1109/MIC.2014.88
http://www.software.ac.uk/resources/publications/better-software-better-research
The document discusses the creation of a wiki catalogue to catalog open source toolkits and testbeds related to software defined networking (SDN), network function virtualization (NFV), mobile edge computing (MEC) and 5G technologies. It notes that there are many toolkits and testbeds but a lack of visibility among researchers. A wiki is proposed to provide a centralized place for researchers, students and developers to discover relevant tools and testbeds. The wiki is being developed in phases, beginning with data collection and developing the initial structure, then opening it for community contributions and updates.
Presentation on "Practical Competences in Engineering and Technology Enhanced Learning: MOOCs and Emerging Areas at the IEEE Education Society" from the IEEE Education Society Special Technical Community on Learning Sciences at the The Chinese University of Hong Kong
Presentation of the paper Creating a distributed mobile networking testbed environment - through the Living Labs approach, Proceedings of 2nd International IEEE/Create-Net Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TridentCom), Barcelona, Spain, March, 2006.
PROnet is an NSF-supported research project being conducted by researchers at the University of Texas at Dallas. PROnet is dedicated to enabling the design, development, demonstration and deployment of innovative ultrahigh-speed low-latency applications being created in and across North Texas and beyond.
Analyzing Big Data in Medicine with Virtual Research Environments and Microse...Ola Spjuth
This document discusses analyzing big data in medicine using virtual research environments and microservices. It notes the vast amount of data being generated and challenges of data management, analysis and scaling. The European Open Science Cloud aims to enable access to shared scientific data across borders. Contemporary analysis uses high-performance computing but has limitations. Cloud computing, virtual machines, containers and microservices can help address these challenges by providing on-demand resources and decomposing functionality into independent services. The PhenoMeNal project is building a standardized e-infrastructure using these approaches to enable users to access tools and data. This improves sustainability, reliability, scalability and enables agile development and science.
Widget and Smart Devices. A Different Approach for Remote and Virtual labsUNED
A vast number of learning content and tools can be found over Internet. Currently, most of them are ad-hoc solutions which are developed for a particular learning platform or environment. New concepts, such as Widgets, Smart devices, Internet of Thing and learning Clouds, are ideas whose goals is the creation of shareable online learning scenarios over different devices and environments.
German Conference on Bioinformatics 2021
https://gcb2021.de/
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
Elsevier‘s RDM Program: Habits of Effective Data and the Bourne UlitmatumAnita de Waard
Elsevier's RDM Program: Ten Habits of Highly Effective Data
The document outlines Elsevier's research data management (RDM) program and efforts to support the effective management of research data. It discusses a "Maslow hierarchy" with 10 aspects of highly effective research data from stored to integrated. It provides examples of Elsevier's RDM tools and services like Hivebench, Mendeley Data, and DataSearch that help support storing, sharing, citing, and discovering research data. It also discusses collaborative RDM efforts like Force11, Research Data Alliance, and Crossref as well as journal initiatives to improve reproducibility. The document concludes with a proposed partnership where an institution could pilot and provide feedback on Elsevier's
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
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1. Standardization of Online Laboratories Why and How?
Hamadou Saliah-Hassane
Professor TELUQ University
Science and Technology Department
Chair of the IEEE-SA P1876 Working Group
hsaliah@ieee.org
2. IEEE SA P1876 Working Group
Chair: Hamadou Saliah-Hassane
Editorial board: John Shokley, Hamadou
Saliah-Hassane, Denis Gillet, Miguel
Rodriguez Artacho, Pablo Orduña,
Janusz Zalewski
hsaliah@ieee.org
https://ieee-sa.centraldesktop.com/1876public/
http://sites.ieee.org/sagroups-edusc/
Networked Smart Learning Objects for Online Laboratories
3. IEEE SA P1876™ Working Group
Contributors to this presentation:
Hamadou Saliah-Hassane
• Denis Gillet (EPFL), John Shockley (ARM),
Manuel Castro (UNED), Luis Felipe Zapata
(FAU), Miguel Rodriguez Artacho (UNED),
Lucas Mellos Carlos (UFSC), Zuzana
Fabusova (Quanser). Wissam Halimi
(EPLF), Maria-Larondo Petrie (FAU),
Christopje Salzmann (EPFL), Elio San
Cristobal (UNED). Pedro Preredes (UNED),
José Pedro Schardosim Simão, João Paulo
Cardoso de Lima, Gustavo Alves, Juarez
Bento Silva and João Bosco da Mota Alveshttp://sites.ieee.org/sagroups-edusc/
Networked Smart Learning Objects for Online Laboratories
4. IEEE SA P1876 Working Group Member
PROFILES (Groups & Consortiums)
• PROLEARN: European Project in the framework of FP7
• Interoperability for searching Learning Object Repositories: The ProLearn Query
Language – Metadata for Learning Object
• GOLC: Global Online Laboratory Consortium (2009 -) -"The mission of the
consortium is the creation of sharable, online experimental environments which
increase the educational and scientific value of learning which may not be
accessible, scalable or efficient through traditional methods.“
• http://www.online-engineering.org/GOLC_about.php - The International
Association of Online Engineering (IAOE) – Development of Online
Engineering
• LiLa: Library of Labs; an initiative of eight universities and three enterprises, for
the mutual exchange of and access to Online Labs
Networked Smart Learning Objects for Online Laboratories
5. IEEE SA P1876 Working Group Member
PROFILES (Groups & Consortiums)
• LORNET: Pan Canadian Project Founded by NSERC
• Interoperability of Learning Object – LO Repositories – TELOS – Instructional
Design Software - Online Labs integration for Distance Education and Research
• Go-Lab: Lab by Experience - “The Go-Lab project aims to encourage
young people to engage in science topics, acquire scientific inquiry skills,
and experience the culture of doing science by undertaking active guided
experimentation”; http://www.go-lab-project.eu/
• RexLab: Remote Experimental Lab – (1997 -) the Remote at the Federal
University of Santa Catarina in Brazil (UFSC) http://rexlab.ufsc.br/en/
Networked Smart Learning Objects for Online Laboratories
6. IEEE SA P1876 Working Group Member
PROFILES (Services, Software & Hardware)
Individual members of the group use products and services they
developed or mutally developed by their partners in our choosen
approach of Research & Development of the P1876™ Draft.
iLab – Shared Architecture (ISA) - First developed at MIT
VISIR –Virtual Instrument Systems in Reality - First developed at Blekinge
Institute of Technology http://openlabs.bth.se/
WebLab Deusto – Labsland - http://weblab.deusto.es/website/
GRAASP – Developed at École Polytechnique Fédérale de Lausanne - http://graasp.eu/
Insdustrial Partners: ARM: https://www.arm.com/research-education/university ; NI: ni.com;
MathWorks™… & Cloud Software Providers
Networked Smart Learning Objects for Online Laboratories
25. Lab@Home
• Students access and manipulate the labs, create laboratory
in order to share devices and interact with other users
during the experimentation process. The workspaces are
created by the own students, who can also edit
information and add other members.
• Among the functionalities available in the collaboratories
are user management (user status, adding and removing),
file sharing, chat room and tasks management (creating,
assigning, completing and due to).
26. Lab@Home
• The collaboratories can also be created from project
templates defined by teachers, with specific tasks and files.
• A specific interface for the laboratory can also be defined
by the teacher in the project creation, so in an assignment,
for example, all students in a course can have the same
resources.
27. Example of Mobile Laboratory Infrastructure
Mini-robots
(Autonomous or
Robots Arms)
Internet
C3230
Mobile Router
WMIC =
WiFi Bridge
Fast Ethernet
Switch
WiFi Access Point
Bluetooth
Access Point
C3230ENC-
1WMIC-K9V01
CONSOLE
10/100 BASE T
12/24 VDC
6A MAX
ETHINPUT
AUX
LINK ACT
---
LINK LINK
LINK
ACT ACT
ACT0
1
2
3
OUTPUT
---5DVC
0.2A MAX
LINK
ACT
OK
Command
/Supervision
Supervision/
Data Acquisition
Cellular Phone
With bluetooth=
GPRS Modem
PAN
WLAN
Sensor Networks
(temperature,
acceleration, etc.)
ONLINE LABORATORY
Cellular Network with
Mobile Internet Access
Public / Private WiFi
VerticalRelayed/Transmitted
Information
NGOM, Ibrahima; Saliah-Hassane, Hamadou; and Lishou, Claude, "Mobile Laboratory Model for Next-Generation
Heterogeneous Wireless Systems," In Robotics: Concepts, Methodologies, Tools, and Applications. IGI Global, 2014,
Pp. 1644-1661. doi:10.4018/978-1-4666-4607-0.ch080.
28. Mobile laboratories as an alternative to
conventional remote laboratories
Hamadou Saliah-Hassane, José Pedro Schardosim Simão,
João Paulo Cardoso de Lima, Gustavo Alves, Juarez Bento Silva and João
Bosco da Mota Alves
LACCEI 2017 – The OAS Summit of Engineering for the Americas
29. • The concept around mobile laboratories has been explored
for quite some time now, and interpreted in different ways
by researchers.
• One of the recurring approaches is associated with the
traditional conception of remote experimentation, making
use of mobile devices to access and manipulate labs in
different locations through the internet.
• On the other hand, the idea we have of mobile labs is
more related to the device under control being mobile,
and hosted by the student.
Mobile Laboratories
30. Experimentation in Online
Environments
• Depending on the experiment’s location and nature (how
real or virtual it is), online labs are usually classified as
virtual, remote or hybrid laboratories
31. Sharing Resources
• Lab Equipment (affordance)
• Managers /Teachers / Lab Tutors / Facilitators
• Students /Learners
• Contents and Learning Scenarios
Collaborative Learning / Teaching / Flippled Classrooms/
Pedagogical Sound
• Delivery Environments (Moodle, WebCT, Sakaï etc)
• Communication Tools: Knowledge Modelers, White Boards, Email,
Chat etc.
Federation – Brokerage of Online Labs
• Networking – Security – Management – Pedagocical needs
• Cyber physical Systems – Online or Networked Embedded Systems
– Complex Systems – Interoperability – Compliance
(manufacturers)
Why a Standard for Online Laboratories for
Education
32. IEEE Standard Development Process Flow
Study Group /
Industry?
Connection
Initiative?
Project
Authorization
Request
PAR
34. IEEE Standard Development Life Cycle
P1876™ is Sponsored
by IEEE Education
Society since 2011
Individual vs Entity
35. IEEE Standard Development Life Cycle (2)
Stakeholders
Observers
Contributors
Drivers-Leaders
Policies and Proceedures (P&P)
36. IEEE Standard Development Life Cycle (3)
• Volunteers
collaborative 1st
draft
• Editorial Board
• Frequent online and
face to face meetings
& Workshops
• Editor in Chief from
ARM
https://standards.ieee.org/develop/index.html
38. Scope of P1876™
The standard defines methods for storing and retrieving
learning objects for online laboratories. The standard will also
define methods for linking learning objects to design and
implement smart learning environments for remote online
laboratories. These objects are, for example, interfaces for
devices connected to user computers over computers
networks and the devices themselves. They are also learning
scenarios or collaboration tools for communications necessary
to conduct an activity of practical online laboratory work; to
design and implement mechanisms that make smart learning
environment formed by the ad hoc aggregation of learning
objects taking into account the pedagogical context for their
use.
39. User Interfaces as Services
• Widget approach (Opensocial applications)
• Based on Interchageable Virtual Instrument (IVI) specification
40. Distributed Instruments and Documents Stored in a PALOMA
Repository
Online Laboratory Repositories - Metadata
41. User Interfaces as Services
• Widget approach (Opensocial aplications)
• Based on IVI specification
Spectrum Analyser Server
(Service Web)
Agilent Spectrum Analyser E4411B
VISA-COM, IntuiLink & Other
Socket
Shared
Variables
SOAP
Network Interfaces to
access to the instrument
Server
Dynamic interaction with
the instrument
APIs Access to the
Instrument
Real Device
Internet Protocol
Spectrum Analyser Clients
(Java Applets Java hosted in web page, Scripts de
Web Server Scripts, Standard Windows
Applications, Applications for PDA)
TELOS
Connector
User Interfaces
43. Laboratory Typology
Local lab: physical location that accommodates users while
allowing them to perform their tasks using equipment or not.
The equipment is often referred to as the experiment (the
object of experimentation). The place may be designated a
room or a natural environment.
44. Laboratory Typology (cont)
Distributed interactive simulations: it carries clusters of
networked computers to provide users with a learning
environment otherwise unattainable in a context of self-
study using a single computer. Here, the simulation can
represent systems to predict their behavior in various
contexts of use. In general, interactive simulations, design,
analysis and visualization assisted by computers go together.
45. Laboratory Typology (cont)
Virtual Lab: modular experimental simulations of scenarios designed
to be implemented from one or more computers. Mathematical models are put
to work to get as close to the credibility of simulations representing theoretical
concepts or real devices. In some cases, it is not possible to simulate scenarios
and experimental behavior of real devices. This is where mathematical models
are too complex, lack of availability of computing power or when the computer
processing time is long. We then use the remote laboratory
46. Laboratory Typology (Cont)
Remote laboratory: a set of network-connected
physical devices that can be observed and controlled at
distance over computer networks. It makes posible
collaborative experiments by interacting with real devices
that are either instruments and / or remote real
mechanisms. A physical object remotely accessible and being
the focus of the observation and / or the experimentation
47. New Trends: Mobile Laboratories
• By using mobile laboratories in collaborative scenarios,
multiple groups are able to perform the same experiment
at the same time, users can pause sessions and resume at
any time without resetting the lab or waiting for other
users.
• In order to develop a common application layer for mobile
laboratories, compatible with different rigs and clients.
• The model Lab as a Service (LaaS) proposes that online
laboratories be delivered as a service able to exchange and
use information from different systems and services.
48. New Trende: Mobile
Laboratories
• By using mobile laboratories in collaborative scenarios,
multiple groups are able to perform the same experiment
at the same time, users can pause sessions and resume at
any time without resetting the lab or waiting for other
users.
• In order to develop a common application layer for mobile
laboratories, compatible with different rigs and clients.
• The model Lab as a Service (LaaS) proposes that online
laboratories be delivered as a service able to exchange and
use information from different systems and services.
49. New Tools: Assessing Learning
Experience in Mobile Labs
• Assessing students’ learning outcome is crucial when
performing laboratory activities in online environments.
• In the mobile labs scenario, where the learning experience
is student-centered, the teacher needs feedback in order
to determine if the experiment had the expected outcome
and if the students learned the skills necessary in that
scenario.
• Assessment is also a problem when using labs in large
courses or MOOCs, requiring considerable effort and time
from teachers and tutors.
50. Assessing Student’s Learning
Experience In Mobile Labs
• The use of Experience API (xAPI), previously known as
TinCan API, enables the easy discovery of learning
behavior by making possible the formalization, storage and
retrieval of learning experiences
• A learning experience in xAPI is tracked and formatted into
a statement, in which an actor performed an action in an
object (actor + verb + activity + additional properties).
• This statement is then stored in a Learning Record Store
(LRS), from where it can be posteriorly retrieved and
analyzed.
51. Solution Prototype
• The proposed solution is composed by four main
components: Smart Device, Lab Gateway, Learning Record
Store (LRS), using a Lab@Home Concept, a collaborative
learning environment (aggregation of required
components).
52. Work in Progress on the
Standardization of Online
Laboratories for Education
eMadrid Session
www.emadridnet.org
26-Nov-2015 REV Conference, Madrid
Miguel R. Artacho
miguel@lsi.uned.es
55. Standardization Layers
Learning environments or learning object repositories
Interactive Open Educational Lab (OEL)
Lab as an OER (LaaO)
Smart Device
Lab as a Service (LaaS)
Courses
Scenarios
Activities
Support material, Personalized, user interfaces, task sequences, paths
Standard:
MLR extension
xAPI extension
Standard:
Service metadata
Services
Protocols
Online Lab
=
Object
Actions
Traces
Sensor Data
State log
Knowledge
Learning
outcome
Layer 1
Embedded Things
Layer 2
Embedded pedagogy
Apparatus, sensors, actuators,
instruments, controllers, embedded
server computer or microcontroller
User prefs
Context
LTI
Configuration
Actuator data
57. Laboratory as a Service (LaaS)
Metadata
• General information on the online lab, including its name,
description or contact information.
• List of APIs to access the services (i.e., actuators service).
• The authorization mechanisms, to allow access to the
described services only by the granted users.
• The concurrent access mechanisms, to manage multiple
access at the same time to the same resource
58. Laboratory as a Service (LaaS)
Functionalities
• Authentication functionality
• Self and known state functionality
• Security and local control
• Logging and alarms
Protocols
• HTTP (to get metadata)
• WebSocket (for interaction with the online lab)
59. The Learning Object model and the
Online Laboratories
• In the e-learning arena, online laboratories could be linked with
the general concept of learning activity: “any activities of an
individual organized with the intention to improve his/her
knowledge, skills and competence”.
• There are standards and specifications that cover the
interoperability of a subset of the following specific features of the
learning objects:
• Description and tagging: metadata;
• Content structuring and packaging;
• Communication;
• Sequencing;
• Learning tools and services interoperability;
• Learning Design.
61. xAPI Learner Experience
Learning activity described using ADL Training and
Learning Architecture (TLA)
Student activity stored in LRS (Learning Record Store)
LRS and LMS communicate through API called eXperience
API (xAPI)
http://sites.ieee.org/sagroups-ltsc/
https://www.tagxapi.org/
63. Embedded lab in LMS (layer 3)
LMS Online lab
LRS
(Call via URL)
xAPI
statements
xAPI statements
(CMI5 spec, in
progress)
64. xAPI
The Remote Laboratory Management System uses the LRS to store the collected
data. The information is sent in a statement including: actor, verb and object.
Actors defined for the prototype are:
• Student A
• Student B
The basic verbs (using ADL Verbs) reported for the lab are:
• Logged-in
• Logged-out
• Interacted
Objects:
• Pole, LED0, LED1, LED2, Reset)
• Python Code
• LAB X Activity Y
71. Basketball game demo experiment
(Hybrid lab Activities integrating the use of the
student lab kit to count point of the game)
72. IEEE-SA Industry Connection Initiative
The IC program offers an efficient, economical environment for
building consensus and producing shared results. Industry
Connections empowers groups with a customizable menu of IEEE
and IEEE-SA resources to produce "fast-track" content and
deliverables such as:
Proposals for standards
• White papers
• Peer-reviewed guides and position papers
• Conferences, workshops and other events
• Databases and registration services
• Software, tools and web services
• Other jointly developed results
73. IEEE SA P1876™ Industry Collaboration
http://standards.ieee.org/develop/indconn/
Networked Smart Learning Objects for Online Laboratories
The IEEE Standards Association (IEEE-SA)
Industry Connections (IC) program helps
incubate new standards and related
products and services by facilitating
collaboration among organizations and
individuals as they hone and refine their
thinking on rapidly changing technologies.
74. Standardization of Online Laboratories Why and How?
Hamadou Saliah-Hassane
Professor TELUQ University
Science and Technology Department
Chair of the IEEE-SA P1876 Working Group
hsaliah@ieee.org