Presentation by Hugo Leroux and Liming Zhu, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Kelly Hart, ONDC in PM&C, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Investigator-initiated clinical trials: a community perspectiveARDC
Presentation by Miranda Cumpston, ACTA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Steve McEachern, ADA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
International perspective for sharing publicly funded medical research dataARDC
Presentation by Olivier Salvado, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Prof Lisa Askie, ANZCTR, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Hugo Leroux and Liming Zhu, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Kelly Hart, ONDC in PM&C, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Investigator-initiated clinical trials: a community perspectiveARDC
Presentation by Miranda Cumpston, ACTA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Steve McEachern, ADA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
International perspective for sharing publicly funded medical research dataARDC
Presentation by Olivier Salvado, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Prof Lisa Askie, ANZCTR, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Adrian Burton, ARDC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Davina Ghersi, NHMRC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Digital transformation to enable a FAIR approach for health data scienceVarsha Khodiyar
Invited talk for ConTech Pharma on 1st March 2022
Abstract
Health Data Research UK is the UK’s national institute for health data science, with a mission to unite the UK’s health data to enable discoveries that improve people’s lives. In this talk, Dr Varsha Khodiyar will outline how HDR UK is bringing together disparate health data from all four countries of the United Kingdom, creating the infrastructure to enable discovery of and access to health data, and the convening standards making bodies to improve data linkage and data reuse. Varsha will also discuss how HDR UK is moving beyond the traditional confines of FAIR data to also ensure that data sharing and data use is transparent and ‘fair’ for the patients and lay public who are the subjects of these datasets.
BigInsight seminar on Practical Privacy-Preserving Distributed Statistical Co...Statistisk sentralbyrå
Seminar Monday March 5th 2018 by BigInsight and Statistics Norway: Presentation by Kassaye Yitbarek Yigzaw. Distributed data analysis in the face og privacy concerns.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
Clinical Data Models - The Hyve - Bio IT World April 2019Kees van Bochove
Population genetics and genomics is an emerging topic for the application of machine learning methods in healthcare and biomedical sciences. Currently, several large genomics initiatives, such as Genomics England, UK Biobank, the All of Us Project, and Europe's 1 Million Genomes Initiative are all in the process of making both clinical and genomics data available from large numbers of patients to benefit biomedical research. However, a key challenge in these initiatives is the standardization of the clinical and outcomes data in such a way that machine learning methods can be effectively trained to discover useful medical and scientific insights. In this talk, we will look at what data is available at scale, and review some of examples of the application of common data and evidence models such as OMOP, FHIR, GA4GH etc. in order to achieve this, based on projects which The Hyve has executed with some of these initiatives to harmonize their clinical, genomics, imaging and wearables data and make it FAIR.
Open science and medical evidence generation - Kees van Bochove - The HyveKees van Bochove
Presentation about open science, the FAIR principles, and medical evidence generation with the OHDSI COVID-19 study-a-thon as an example. I've used variations on this deck in a couple of classroom and online courses for PhD and master students early 2020.
BioSHaRE: The DataSHIELD Legal Analysis Template - Susan Wallace - University...Lisette Giepmans
BioSHaRE conference July 28th, 2015, Milan - Latest tools and services for data sharing
Stream 2: ELSI approaches and services
An ethico-legal analysis was conducted at ULEIC that examined each step of the DataSHIELD process from the perspective of UK case law, regulations, and guidance. In order to facilitate a similar analysis for other countries/ jurisdictions, a ‘DataSHIELD Legal Analysis Template’ is being made. Contact: sew40@leicester.ac.uk
DataSHIELD was born of the requirement in the biomedical and social sciences to co-analyse individual patient data (micro data) from different sources, without disclosing identity or sensitive information. Under DataSHIELD, raw data never leave the data provider and no micro data or disclosive information can be seen by the researcher. The analysis is taken to the data – not the data to the analysis. It provides a flexible, modular, open-source solution ideally placed to serve a broad user and development community and to circumvent barriers related to ethical-legal restrictions, intellectual property and physical size of the data as a limiting factor.
Kuchinke Clinical Trials Networks supported by tools and servicesWolfgang Kuchinke
Clinical Trials Networks supported by Tools and Services from Infrastructure Projects.
International clinical trials are a challenge to management. Though, the number of clinical trials worldwide is increasing by around 10% per year, approvals for new molecule entities and biomedical licenses show little long-term increase. Main challenges are the need to recruit and retain sufficient numbers of patients and the successful implementing e-Clinical Trials technologies, especially for trials incorporating ePRO (patient reported outcome) and eRecruitment services. We suggest that clinical trials networks should cooperate with infrastructure projects to enable the implementation of eTrials and patient-centric trials.
Clinical trials systems can be optimised by coordination through information sharing and collaboration and by building networks. Here infrastructures can function as enablers by the provision of
software tools, especially patient centric trials, ePRO (Patient Reported Outcome) and data collection and recruitment using EHRs (Electronic Health Records) and the implementation of nessessary data protection, privacy protection and identity management. As example for a clinical trials network ECRIN is addressed. ECRIN is a public, non-profit organisation that links scientific partners and networks across Europe to facilitate multinational clinical research. We suggest the integration of clinical research at ECRIN with several infrastructure services developed by BBMRI, EATRIS, EUDAT, TransForm, p-medicine, BioMedBridges, etc., resulting in an increase in interoperability of clinical data management, biobanking, genetic databases, Electronic Health Records (EHR), query systems, data warehouses, data repositories and imaging data.
Data sharing promotes many goals of the NIH research endeavor. It is particularly important for unique data that cannot be readily replicated. Data sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Do you know what a data sharing plan should include? Are you aware of common practices and standards for data sharing? Do you know what services are available to help share your data responsibly? This workshop will begin to address these questions. Q&A will follow the presentation. Anyone interested in or planning to apply for NIH funding should attend. Note: The NIH data-sharing policy applies to applicants seeking $500,000 or more in direct costs in any year of the proposed research.
Presentation by Dr Adrian Burton, ARDC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Davina Ghersi, NHMRC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Digital transformation to enable a FAIR approach for health data scienceVarsha Khodiyar
Invited talk for ConTech Pharma on 1st March 2022
Abstract
Health Data Research UK is the UK’s national institute for health data science, with a mission to unite the UK’s health data to enable discoveries that improve people’s lives. In this talk, Dr Varsha Khodiyar will outline how HDR UK is bringing together disparate health data from all four countries of the United Kingdom, creating the infrastructure to enable discovery of and access to health data, and the convening standards making bodies to improve data linkage and data reuse. Varsha will also discuss how HDR UK is moving beyond the traditional confines of FAIR data to also ensure that data sharing and data use is transparent and ‘fair’ for the patients and lay public who are the subjects of these datasets.
BigInsight seminar on Practical Privacy-Preserving Distributed Statistical Co...Statistisk sentralbyrå
Seminar Monday March 5th 2018 by BigInsight and Statistics Norway: Presentation by Kassaye Yitbarek Yigzaw. Distributed data analysis in the face og privacy concerns.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
Clinical Data Models - The Hyve - Bio IT World April 2019Kees van Bochove
Population genetics and genomics is an emerging topic for the application of machine learning methods in healthcare and biomedical sciences. Currently, several large genomics initiatives, such as Genomics England, UK Biobank, the All of Us Project, and Europe's 1 Million Genomes Initiative are all in the process of making both clinical and genomics data available from large numbers of patients to benefit biomedical research. However, a key challenge in these initiatives is the standardization of the clinical and outcomes data in such a way that machine learning methods can be effectively trained to discover useful medical and scientific insights. In this talk, we will look at what data is available at scale, and review some of examples of the application of common data and evidence models such as OMOP, FHIR, GA4GH etc. in order to achieve this, based on projects which The Hyve has executed with some of these initiatives to harmonize their clinical, genomics, imaging and wearables data and make it FAIR.
Open science and medical evidence generation - Kees van Bochove - The HyveKees van Bochove
Presentation about open science, the FAIR principles, and medical evidence generation with the OHDSI COVID-19 study-a-thon as an example. I've used variations on this deck in a couple of classroom and online courses for PhD and master students early 2020.
BioSHaRE: The DataSHIELD Legal Analysis Template - Susan Wallace - University...Lisette Giepmans
BioSHaRE conference July 28th, 2015, Milan - Latest tools and services for data sharing
Stream 2: ELSI approaches and services
An ethico-legal analysis was conducted at ULEIC that examined each step of the DataSHIELD process from the perspective of UK case law, regulations, and guidance. In order to facilitate a similar analysis for other countries/ jurisdictions, a ‘DataSHIELD Legal Analysis Template’ is being made. Contact: sew40@leicester.ac.uk
DataSHIELD was born of the requirement in the biomedical and social sciences to co-analyse individual patient data (micro data) from different sources, without disclosing identity or sensitive information. Under DataSHIELD, raw data never leave the data provider and no micro data or disclosive information can be seen by the researcher. The analysis is taken to the data – not the data to the analysis. It provides a flexible, modular, open-source solution ideally placed to serve a broad user and development community and to circumvent barriers related to ethical-legal restrictions, intellectual property and physical size of the data as a limiting factor.
Kuchinke Clinical Trials Networks supported by tools and servicesWolfgang Kuchinke
Clinical Trials Networks supported by Tools and Services from Infrastructure Projects.
International clinical trials are a challenge to management. Though, the number of clinical trials worldwide is increasing by around 10% per year, approvals for new molecule entities and biomedical licenses show little long-term increase. Main challenges are the need to recruit and retain sufficient numbers of patients and the successful implementing e-Clinical Trials technologies, especially for trials incorporating ePRO (patient reported outcome) and eRecruitment services. We suggest that clinical trials networks should cooperate with infrastructure projects to enable the implementation of eTrials and patient-centric trials.
Clinical trials systems can be optimised by coordination through information sharing and collaboration and by building networks. Here infrastructures can function as enablers by the provision of
software tools, especially patient centric trials, ePRO (Patient Reported Outcome) and data collection and recruitment using EHRs (Electronic Health Records) and the implementation of nessessary data protection, privacy protection and identity management. As example for a clinical trials network ECRIN is addressed. ECRIN is a public, non-profit organisation that links scientific partners and networks across Europe to facilitate multinational clinical research. We suggest the integration of clinical research at ECRIN with several infrastructure services developed by BBMRI, EATRIS, EUDAT, TransForm, p-medicine, BioMedBridges, etc., resulting in an increase in interoperability of clinical data management, biobanking, genetic databases, Electronic Health Records (EHR), query systems, data warehouses, data repositories and imaging data.
Data sharing promotes many goals of the NIH research endeavor. It is particularly important for unique data that cannot be readily replicated. Data sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Do you know what a data sharing plan should include? Are you aware of common practices and standards for data sharing? Do you know what services are available to help share your data responsibly? This workshop will begin to address these questions. Q&A will follow the presentation. Anyone interested in or planning to apply for NIH funding should attend. Note: The NIH data-sharing policy applies to applicants seeking $500,000 or more in direct costs in any year of the proposed research.
Day 1_Session3_TRIPS_WASDS_ICRISAT - This presentation outlines planned ICRISAT activities for the CGIAR Research Program on Dryland Systems for the West African Sahel and Dry Savannas region.
Day 1_Session3_TRIPS_WASDS_Bioversity - This presentation sets out the planned research activities of Bioversity in action sites of the West African Sahel and Dry Savannas target region.
The TRIPS meeting for North Africa and West Asia took place from July 26 to 28. This presentation, presented by Dr. Ali Nefzaoui, Dr. Rachid Serraj, Dr. Maarten van Ginkel, and Dr. William Payne covered NA & WA Target Area and action site characterization. Basic descriptors included climate, topography, soils, water resources, land use/land cover, land degradation, demography, agricultural systems, governance, and research opportunities. Sites were delineated into high potential areas which are mainly cereal and fruit tree based and low potential areas which are mainly agropastoral and pastoral systems.
The presentation outlines means of reducing vulnerability and managing risk in high and low potential areas and describes their climate regimes. It also identifies constraints, hypothesis and outputs for both types of areas. Low potential area constraints include high population growth, limited water resources, transitional production systems, more frequent and prolonged droughts and inappropriate policies of land use.
Constraints for high production areas (areas in which sustainable intensification for more productive, profitable and diversified dryland agriculture with well established linkages to markets) include pressure to be efficient in order to compete globally, small farms inability to benefit from economies of scale and youth preference to transition to cities for livelihoods.
dkNET Webinar: Creating and Sustaining a FAIR Biomedical Data Ecosystem 10/09...dkNET
Abstract
In this presentation, Susan Gregurick, Ph.D., Associate Director of Data Science and Director, Office of Data Science Strategy at the National Institutes of Health, will share the NIH’s vision for a modernized, integrated FAIR biomedical data ecosystem and the strategic roadmap that NIH is following to achieve this vision. Dr. Gregurick will highlight projects being implemented by team members across the NIH’s 27 institutes and centers and will ways that industry, academia, and other communities can help NIH enable a FAIR data ecosystem. Finally, she will weave in how this strategy is being leveraged to address the COVID-19 pandemic.
Presenter: Susan Gregurick, Ph.D., Associate Director of Data Science and Director, Office of Data Science Strategy at the National Institutes of Health
dkNET Webinar Information: https://dknet.org/about/webinar
On November 21st 2014 at the Tufts University Medford campus and November 25th 2014 at the campus of the University of Massachusetts Medical School in Worcester, the BLC and Digital Science hosted a workshop focused on better understanding the research information management landscape.
Mark Hahnel, CEO of Figshare discussed more specific aspects of the research data management landscape and various approaches to address the growing suite of mandates.
Building an Intelligent Biobank to Power Research Decision-MakingDenodo
This presentation belongs to the workshop: "Building an Intelligent Biobank to Power Research Decision-Making", from ISBER 2015 Annual Meeting by Lori A. Ball (Chief Operating Officer, President of Integrated Client Solutions at BioStorage Technologies, Inc), Brian Brunner (Senior Manager, Clinical Practice at LabAnswer) and Suresh Chandrasekaran (Senior Vice President at Denodo).
The workshop cover three different topic areas:
- Research sample intelligence: the growing need for Global Data Integration (Biobank Sample and Data Stakeholders).
- Building a research data integration plan and cloud sourcing strategy (data integration).
- How data virtualization works and the value it delivers (a data virtualization introduction, solution portfolio and current customers in Life Sciences industry).
The biomedical R&D environment is increasingly dependent on data meta-analysis and bioinformatics to support research advancements. The integration of biorepository sample inventory data with biomarker and clinical research information has become a priority to R&D organizations. Therefore, a flexible IT system for managing sample collections, integrating sample data with clinical data and providing a data virtualization platform will enable the advancement of research studies. This workshop provides an overview of how sample data integration, virtualization and analytics can lead to more streamlined and unified sample intelligence to support global biobanking for future research.
This presentation was provided by Kristen Ratan, Founder of Stratos and CoFounder of ICOR, and served as the opening keynote for the two-day "NISO Tech Summit: Reflections Upon The Year of Open Science." Day one was held on October 25, 2023.
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...dkNET
For all proposals submitted on/after January 25 2023, NIH will require the sharing of data from all NIH funded studies. Do you have appropriate data management practices and sharing plans in place to meet these requirements? Have questions or need some help? Join the dkNET office hours to learn about NIH’s policy (NOT-OD-21-013) and resources that could help.
*Previous Office Hours Slides and Recording: https://dknet.org/rin/research-data-management
Upcoming Webinars Schedule: https://dknet.org/about/webinar
Management of research data specifically for Engineering and Physical Science. Delivered by Stuart Macdonald at the "Support for Enhancing Research Impact" meeting at the University of Edinburgh on 22 June 2016.
Presentación de Joy Davidson, Digital Curation Centre (UK) en FOSTER event: Data Management Plan and Social Impact of Research. Universitat Jaume I, 27 mayo 2016
This presentation was provided by Dr. Paul Burton of the University of Bristol during the NISO Symposium, Privacy Implications of Research Data, held on September 11, 2016, in conjunction with the International Data Week in Denver, Colorado.
This presentation was provided by Maria Praetzellis of California Digital Library, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Compliance: Data Management Plans and Public Access to DataMargaret Henderson
Presented at The 8th Annual University of Massachusetts and New England Area Librarian e-Science Symposium, Wednesday, April 6, 2016
University of Massachusetts Medical School
What is Data Commons and How Can Your Organization Build One?Robert Grossman
This is a talk that I gave at the Molecular Medicine Tri Conference on data commons and data sharing to accelerate research discoveries and improve patient outcomes. It also covers how your organization can build a data commons using the Open Commons Consortium's Data Commons Framework and the University of Chicago's Gen3 data commons platform.
Presentation given by Sarah Jones at a seminar run by LSHTM on 6th November 2012. http://www.lshtm.ac.uk/newsevents/events/2012/11/developing-data-management-expertise-in-research---half-day-event
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
What is greenhouse gasses and how many gasses are there to affect the Earth.
Shifting the goal post – from high impact journals to high impact data
1. Shifting the goal post – from high
impact journals to high impact data
Anja Gassner,
World Agroforestry Centre (ICRAF)
2. The policy is applicable both to new data as well as retrospectively to legacy data:
1. Data shall be made open access as soon as possible and in any event within 12 month
of completion of the data collection or appropriate project milestone
2. Existing and future databases shall be made Open access
3. Datasets shall be made open access after the publication the data replicates is
published.
The consortium policy provides two options that allow centers to decide when and
what kind of research data should be made open access
1. data sets that are regarded as not of value to others (draft, poor quality or
incomplete) are excepted from this policy (Section 4.1.1. Openness). This option is
important if data collection is done by partners and is not in our full control.
2. Completion of data collection is a relative term and independent of funding
(unless stated otherwise in the grant contract) and project closure. Thus it is up to
the center to define this on a case by case basis and allows control over the actual
release date.
3. Common Misconceptions
• Open Access means that I share all my data
• Open Access means that I do not have time to
use the data for publications
• Open Access means that I will not be
recognized for my work
• Sharing data means I share all my data
4. The “selfish” scientist?
“Like too many publicly funded ARIs, some
Centre and System-wide programs seem to treat
data as proprietary”
The CGIAR at 31: An Independent Meta-evaluation of the CGIAR (2004)
6. Sharing Data?
• Data that has already been used for a
publication “replication data sets”
• Descriptions about your Data –”Metadata”
7.
8.
9. Data publishing!
Quisumbing A, Baulch B (2010) Chronic Poverty and Long Term Impact Study
in Bangladesh <http://hdl.handle.net/1902.1/17045
UNF:5:8MUn92HhwQhRKF69wSTwaA== International Food Policy Research
Institute [Distributor] V5 [Version]>
10.
11. ICRAF’s Research Data
Management Policy
1. Projects are responsible for ensuring that research
data is described by appropriated Metadata
throughout their lifecycle. Metadata should be
incompliance with the Simple Dublin Core
requirements, or globally accepted metadata standards
for specific data types
2. Every project shall upon closure provide a list of all
data sets produced by the project to the regional
coordinator and the GRP leaders, who will make
recommendation regarding the identification of high
value data sets, both to the Centre and our partners.
These high value data sets shall be submitted to the
institute repository.
3. To improve scientific publications, consensus with
scientific peers and public trust in the quality of our
research outputs the Centre will provide institutional
support to ensure that all necessary raw data will be
made public to reproduce or replicate every scientific
publication that is based on research data. Scientists
are required to submit necessary raw, verified data for
every scientific publication in standard file formats.
12.
13. Open Access?
Open Access is a means to an end
• Better quality data
• Better quality publications
• Higher usage of data (internal & external)
• Higher Recognition for “Techis”
• More transparency
16. RMG Data Quality Workflow
CSPro Application
design
Application
implementation
• Questions & data types
• Checks
• Skips
• Training clerks
Application
Testing
• Test Questions & data types
• Test Checks
• Test Skips
• Data Entry
Validation
• Double data entry
validation check
Validation checks Data entry
validation
• Update data on CSPro
Data
manipulation
Inconsistency
validationInconsistency checks
Archive data
on Dataverse
• Variable & value labels
• Splitting variables
• Extracting tables
• Reshaping data
• Missing values
RMG PROJECT
Data analysis
• Update inconsistencies
17. How to get started
• Research Data Policies at Centre level
• Adoption of OAI-compliant data repositories
• Linking data and publications
• Ethical committee to be established in all Centers
• Clear guidelines on authorship attribution
• Zero tolerance of scientific fraud
• Specific funds to publish high value legacy data
• Building a joint M&I and research method team
18.
19. 1. Unified and streamlined geospatial technologies that can help deliver integrated
systems research on time, while maintaining the highest level of fidelity.
2. Advanced, well-designed, and highly usable products that define new standards for
applying landscape to on-farm applications.
3. Databases, products, and services that support the entire information lifecycle,
transforming multi-source content into dynamic information at frequent intervals.
Agro-Ecosystems (GeoAgro) portal, part of the CRP Drylands Systems
integrated systems research portfolio. This online resource provides
comprehensive information encompassing all geospatial genres in a
streamlined system: remote sensing, GIS, and spatial modeling.
The unique features of GeoAgro portal include: