Unearthed Industry Lead - Crowdsourcing, Holly Bridgwater's presentation from the Copper to the World conference on 18 June 2019 about outcomes of the OZ Minerals Explorer Challenge.
The document discusses TERN, the Terrestrial Ecosystem Research Network, which supports coordinated ecosystem science in Australia through infrastructure and networks. It enables long-term collection, storage, synthesis and sharing of ecosystem data to connect science with policy and management. The Australian Coastal Ecosystems Facility and SEQuITOR project are also summarized as examples of initiatives that leverage TERN's infrastructure to provide access to coastal and southeast Queensland ecosystem data through interactive maps, charts and other tools.
Geoscientific data held by the Australian government is a valuable and strategic resource, The application of open data practices to this data will not only directly benefit the mining and exploration industry and government but also a broad range of professionals and organisations, from farmers to archaeologists, engineers and environmentalists
The document discusses a Faculty Development Program (FDP) on database management systems that was held on December 6, 2018 at the University College of Engineering Tindivanam in Tindivanam, India. The FDP covered recent research perspectives in different database management systems and the importance of database management systems in Digital India. It was conducted by Dr. A. Karthirvel, Professor and Head of the Computer Science and Engineering Department at MNM Jain Engineering College in Chennai.
This document summarizes Nicole Vasilevsky's presentation on teaching data science to undergraduate students. It discusses the need for data science training, the open educational resources (OERs) developed by OHSU Library to address this need, and workshops offered including "Data and Donuts". The OERs cover the entire research process, from finding data to analysis to sharing results. Workshops are hands-on and interactive. Future plans include continuing "Data and Donuts" and potentially a larger OHSU Library Data Science Institute. The overall goal is to provide accessible data science training to address the growing demand.
The art of depositing social science data: maximising quality and ensuring go...Louise Corti
The document provides guidance for depositing data into a research data repository. It discusses incentivizing researchers to share data, developing data policies, reviewing data for quality and disclosure risks, preparing documentation, assigning licenses, and providing support to depositors. The role of the repository manager is to work with depositors to prepare data according to best practices and the repository's standards to ensure long-term preservation and access.
This document summarizes Goldsmiths' efforts to develop a research data management policy. A working group was formed to review existing policies, discuss data storage and training. They drafted a policy addressing the research data lifecycle, responsibilities of researchers, and the college's role in preserving access to data. A data repository was also created. Key recommendations include identifying stakeholders, being practical, and tying the policy to the university's strategic goals. The overall aim is to improve research support through better research data management.
The document discusses TERN, the Terrestrial Ecosystem Research Network, which supports coordinated ecosystem science in Australia through infrastructure and networks. It enables long-term collection, storage, synthesis and sharing of ecosystem data to connect science with policy and management. The Australian Coastal Ecosystems Facility and SEQuITOR project are also summarized as examples of initiatives that leverage TERN's infrastructure to provide access to coastal and southeast Queensland ecosystem data through interactive maps, charts and other tools.
Geoscientific data held by the Australian government is a valuable and strategic resource, The application of open data practices to this data will not only directly benefit the mining and exploration industry and government but also a broad range of professionals and organisations, from farmers to archaeologists, engineers and environmentalists
The document discusses a Faculty Development Program (FDP) on database management systems that was held on December 6, 2018 at the University College of Engineering Tindivanam in Tindivanam, India. The FDP covered recent research perspectives in different database management systems and the importance of database management systems in Digital India. It was conducted by Dr. A. Karthirvel, Professor and Head of the Computer Science and Engineering Department at MNM Jain Engineering College in Chennai.
This document summarizes Nicole Vasilevsky's presentation on teaching data science to undergraduate students. It discusses the need for data science training, the open educational resources (OERs) developed by OHSU Library to address this need, and workshops offered including "Data and Donuts". The OERs cover the entire research process, from finding data to analysis to sharing results. Workshops are hands-on and interactive. Future plans include continuing "Data and Donuts" and potentially a larger OHSU Library Data Science Institute. The overall goal is to provide accessible data science training to address the growing demand.
The art of depositing social science data: maximising quality and ensuring go...Louise Corti
The document provides guidance for depositing data into a research data repository. It discusses incentivizing researchers to share data, developing data policies, reviewing data for quality and disclosure risks, preparing documentation, assigning licenses, and providing support to depositors. The role of the repository manager is to work with depositors to prepare data according to best practices and the repository's standards to ensure long-term preservation and access.
This document summarizes Goldsmiths' efforts to develop a research data management policy. A working group was formed to review existing policies, discuss data storage and training. They drafted a policy addressing the research data lifecycle, responsibilities of researchers, and the college's role in preserving access to data. A data repository was also created. Key recommendations include identifying stakeholders, being practical, and tying the policy to the university's strategic goals. The overall aim is to improve research support through better research data management.
Unlocking the geospatial potential of survey datatomensom
Paper on a JISC-funded project based at the UK Data Archive, as presented at the GISRUK 2012 conference, Lancaster University. The project set out to better enable the use of Archive datasets in GIS, primarily by addressing metadata and quality issues of geospatial identifiers.
These are the slides and text used for webinar given on Wednesday, January 16, 2013 on the new web page for the Life of a Dataset, and depositing data at ICPSR.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
Collaborate, Automate, Prepare, Prioritize: Creating Metadata for Legacy Rese...Jennifer Liss
Data curation projects frequently deal with data that were not created for the purposes of long- term preservation and re-use. How can curation of such legacy data be improved by supplying necessary metadata? In this report, we address this and other questions by creating robust metadata for twenty legacy research datasets. We report on the metrics of creating domain- specific metadata and propose a four-prong framework of metadata creation for legacy research data. Our findings indicate that there is a steep learning curve in encoding metadata using the FGDC content standard for digital geospatial metadata. Our project demonstrates that when data curators are handed research data “as is,” they may be successful in incorporating such data into a data sharing environment. We found that data curators can be successful in creating descriptive metadata and enhancing discoverability via subject analysis. However, curators must be aware of the limitations in applying structural and administrative metadata for legacy data.
Developing core common outcomes for tropical peatland research and managementMark Reed
Presentation by Prof Mark Reed at CIFOR Indonesian to open UN Global Peatland Initiative workshop to identify key variables that should be measured in tropical peatland research and monitoring. Workshop co-facilitated by Mark Reed and Dylan Young, with slides adapted from a presentation by Gav Stewart, Newcastle University.
Accessing data for research: data publishing pathways and the Five SafesLouise Corti
Presented atL Assessing Disclosure Risk in Population Research Data and Outputs, Children of the 90s (ALSPAC)
Bristol Medical School, 24 January 2020.
In this half day session, we introduce the concept of a Safe Health Researcher, where both data producers and users are not only aware of key data legal, ethical and security measures surrounding the management and publication of biomedical research data, but also any risk in outputs they are creating.
The practical training session aimed at aimed at data managers looks at key elements of disclosure risk and trust in sharing biomedical data. We will cover the principles and practicalities of reviewing disclosure risk in numeric data sources and in research outputs.
This document summarizes a presentation about big data. The presentation covered what big data is, the four V's of big data (volume, velocity, variety, and veracity), a brief history of big data, diving deeper into Hadoop and its ecosystem, and two case studies. The presentation also discussed the big data initiative at the company CCC and how it aims to use big data for student success, retention, graduation rates, and improving advising.
This document summarizes a presentation given at IASSIST in Cologne, Germany in May 2013 about the rise of data journals. It discusses the benefits of publishing data in journals, such as increased citations and reuse of data. However, it also notes challenges including linking data to publications and validating data. Several projects are working to address these challenges and facilitate data publication, such as establishing standards for peer reviewing datasets and enabling automatic exchange of metadata between repositories and publishers. Data journals are increasing in various fields and aim to give academic credit to data creators and provide long-term access to datasets.
Data Facilties Workshop - Panel on Global Data Sharing ExemplarsEarthCube
This series of presentations was given at the EarthCube Data Facilities End-User Workshop held January 15-17, 2014 in Washington, DC. This workshop provided a forum to discuss the unique requirements and challenges associated with developing the communication, collaboration, interoperability, and governance structures that will be required to build EarthCube in conjunction with existing and emerging NSF/GEO facilities.
This panel and presentation, specifically, outlined and explained several exemplars in global data sharing, featuring:
Lindsay Powers (CoopEUS)
Tim Ahern (GEO/GEOSS)
Bernard Minster (World Data System)
Beth Plale (Research Data Alliance)
A 25 minute talk from a panel on big data curricula at JSM 2013
http://www.amstat.org/meetings/jsm/2013/onlineprogram/ActivityDetails.cfm?SessionID=208664
Kimberly Silk presented on data management and discovery at the Martin Prosperity Institute. The MPI collects large social science datasets from various common and authoritative sources to support research. To better organize their growing collection, the MPI implemented an open data discovery platform called Dataverse to catalog and provide access to their datasets. Open data initiatives aim to make certain government data freely available to the public, but also present challenges around data preparation, support, and responsiveness. Big data refers to extremely large datasets beyond the capabilities of typical database tools, and data visualization is an important way to communicate insights from data.
This document discusses sharing research data. It describes the Data Services Center, which provides data services including finding and providing access to datasets. It notes that funders and publishers require data sharing, and that shared data receives more citations. It recommends sharing the minimum data needed to reproduce results, and considering timing, usability and granularity of data sharing. For sharing methods, it recommends using disciplinary or general repositories like UR Research, Dryad and REACTUR, which provide long-term preservation and access. Workshops and help are available for data management and sharing.
Introduction to Big Data and Learning Analytics – Resources Joasia van Kooten
This document provides resources on big data and learning analytics divided into four sections. The sections include introductions and overviews of big data and learning analytics, reports on the topics, courses and MOOCs, and videos and webinars. Resources listed include YouTube videos, websites, articles, and a Coursera MOOC on big data in education starting in October 2013.
MEDEAnet webinar Big Data & Learning Analytics ResourcesMEDEA Awards
This document provides resources on big data and learning analytics divided into four sections. The sections include introductions and overviews of big data and learning analytics, reports on the topics, courses and MOOCs, and videos and webinars. Resources listed include YouTube videos, websites, articles, and a Coursera MOOC on big data in education starting in October 2013.
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
Improving Access to Research Data: What does changing legislation mean for y...Marieke Guy
Presentation given at Bett: Technology in Higher Education Conference, Jan 30 - 31
http://www.bettshow.com/Default.aspx?nid=15&refer=17&id=mainLnk2&id1=ssubLnk8
Incentivising the uptake of reusable metadata in the survey production processLouise Corti
This document discusses incentivizing the uptake of reusable metadata in survey production. It notes that there is no universal language used to document survey questions and variables, leading to wasted resources. The Data Documentation Initiative (DDI) is proposed as a standard. Barriers to adopting metadata best practices include legacy systems, manual processes, and reluctance to change. The document outlines ideas to incentivize metadata use such as specifying documentation requirements in funding calls and improving documentation tools and workflows. Showing tangible benefits through applications like question banks and data exploration systems is also suggested.
Use of data in safe havens: ethics and reproducibility issuesLouise Corti
The document discusses ethics and reproducibility issues related to using data in safe havens. It summarizes the UK Data Service, which curates social science data and uses various safeguards to provide access to controlled data through its spectrum of access. It describes legal gateways for data sharing, the Digital Economy Act, and the UK Statistics Authority's accreditation process for researchers and projects. It also discusses the UK Statistics Authority's ethics self-assessment tool and factors that can impact reproducibility when data and code are behind access restrictions in safe havens.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfSelcen Ozturkcan
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Unlocking the geospatial potential of survey datatomensom
Paper on a JISC-funded project based at the UK Data Archive, as presented at the GISRUK 2012 conference, Lancaster University. The project set out to better enable the use of Archive datasets in GIS, primarily by addressing metadata and quality issues of geospatial identifiers.
These are the slides and text used for webinar given on Wednesday, January 16, 2013 on the new web page for the Life of a Dataset, and depositing data at ICPSR.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
Collaborate, Automate, Prepare, Prioritize: Creating Metadata for Legacy Rese...Jennifer Liss
Data curation projects frequently deal with data that were not created for the purposes of long- term preservation and re-use. How can curation of such legacy data be improved by supplying necessary metadata? In this report, we address this and other questions by creating robust metadata for twenty legacy research datasets. We report on the metrics of creating domain- specific metadata and propose a four-prong framework of metadata creation for legacy research data. Our findings indicate that there is a steep learning curve in encoding metadata using the FGDC content standard for digital geospatial metadata. Our project demonstrates that when data curators are handed research data “as is,” they may be successful in incorporating such data into a data sharing environment. We found that data curators can be successful in creating descriptive metadata and enhancing discoverability via subject analysis. However, curators must be aware of the limitations in applying structural and administrative metadata for legacy data.
Developing core common outcomes for tropical peatland research and managementMark Reed
Presentation by Prof Mark Reed at CIFOR Indonesian to open UN Global Peatland Initiative workshop to identify key variables that should be measured in tropical peatland research and monitoring. Workshop co-facilitated by Mark Reed and Dylan Young, with slides adapted from a presentation by Gav Stewart, Newcastle University.
Accessing data for research: data publishing pathways and the Five SafesLouise Corti
Presented atL Assessing Disclosure Risk in Population Research Data and Outputs, Children of the 90s (ALSPAC)
Bristol Medical School, 24 January 2020.
In this half day session, we introduce the concept of a Safe Health Researcher, where both data producers and users are not only aware of key data legal, ethical and security measures surrounding the management and publication of biomedical research data, but also any risk in outputs they are creating.
The practical training session aimed at aimed at data managers looks at key elements of disclosure risk and trust in sharing biomedical data. We will cover the principles and practicalities of reviewing disclosure risk in numeric data sources and in research outputs.
This document summarizes a presentation about big data. The presentation covered what big data is, the four V's of big data (volume, velocity, variety, and veracity), a brief history of big data, diving deeper into Hadoop and its ecosystem, and two case studies. The presentation also discussed the big data initiative at the company CCC and how it aims to use big data for student success, retention, graduation rates, and improving advising.
This document summarizes a presentation given at IASSIST in Cologne, Germany in May 2013 about the rise of data journals. It discusses the benefits of publishing data in journals, such as increased citations and reuse of data. However, it also notes challenges including linking data to publications and validating data. Several projects are working to address these challenges and facilitate data publication, such as establishing standards for peer reviewing datasets and enabling automatic exchange of metadata between repositories and publishers. Data journals are increasing in various fields and aim to give academic credit to data creators and provide long-term access to datasets.
Data Facilties Workshop - Panel on Global Data Sharing ExemplarsEarthCube
This series of presentations was given at the EarthCube Data Facilities End-User Workshop held January 15-17, 2014 in Washington, DC. This workshop provided a forum to discuss the unique requirements and challenges associated with developing the communication, collaboration, interoperability, and governance structures that will be required to build EarthCube in conjunction with existing and emerging NSF/GEO facilities.
This panel and presentation, specifically, outlined and explained several exemplars in global data sharing, featuring:
Lindsay Powers (CoopEUS)
Tim Ahern (GEO/GEOSS)
Bernard Minster (World Data System)
Beth Plale (Research Data Alliance)
A 25 minute talk from a panel on big data curricula at JSM 2013
http://www.amstat.org/meetings/jsm/2013/onlineprogram/ActivityDetails.cfm?SessionID=208664
Kimberly Silk presented on data management and discovery at the Martin Prosperity Institute. The MPI collects large social science datasets from various common and authoritative sources to support research. To better organize their growing collection, the MPI implemented an open data discovery platform called Dataverse to catalog and provide access to their datasets. Open data initiatives aim to make certain government data freely available to the public, but also present challenges around data preparation, support, and responsiveness. Big data refers to extremely large datasets beyond the capabilities of typical database tools, and data visualization is an important way to communicate insights from data.
This document discusses sharing research data. It describes the Data Services Center, which provides data services including finding and providing access to datasets. It notes that funders and publishers require data sharing, and that shared data receives more citations. It recommends sharing the minimum data needed to reproduce results, and considering timing, usability and granularity of data sharing. For sharing methods, it recommends using disciplinary or general repositories like UR Research, Dryad and REACTUR, which provide long-term preservation and access. Workshops and help are available for data management and sharing.
Introduction to Big Data and Learning Analytics – Resources Joasia van Kooten
This document provides resources on big data and learning analytics divided into four sections. The sections include introductions and overviews of big data and learning analytics, reports on the topics, courses and MOOCs, and videos and webinars. Resources listed include YouTube videos, websites, articles, and a Coursera MOOC on big data in education starting in October 2013.
MEDEAnet webinar Big Data & Learning Analytics ResourcesMEDEA Awards
This document provides resources on big data and learning analytics divided into four sections. The sections include introductions and overviews of big data and learning analytics, reports on the topics, courses and MOOCs, and videos and webinars. Resources listed include YouTube videos, websites, articles, and a Coursera MOOC on big data in education starting in October 2013.
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
Improving Access to Research Data: What does changing legislation mean for y...Marieke Guy
Presentation given at Bett: Technology in Higher Education Conference, Jan 30 - 31
http://www.bettshow.com/Default.aspx?nid=15&refer=17&id=mainLnk2&id1=ssubLnk8
Incentivising the uptake of reusable metadata in the survey production processLouise Corti
This document discusses incentivizing the uptake of reusable metadata in survey production. It notes that there is no universal language used to document survey questions and variables, leading to wasted resources. The Data Documentation Initiative (DDI) is proposed as a standard. Barriers to adopting metadata best practices include legacy systems, manual processes, and reluctance to change. The document outlines ideas to incentivize metadata use such as specifying documentation requirements in funding calls and improving documentation tools and workflows. Showing tangible benefits through applications like question banks and data exploration systems is also suggested.
Use of data in safe havens: ethics and reproducibility issuesLouise Corti
The document discusses ethics and reproducibility issues related to using data in safe havens. It summarizes the UK Data Service, which curates social science data and uses various safeguards to provide access to controlled data through its spectrum of access. It describes legal gateways for data sharing, the Digital Economy Act, and the UK Statistics Authority's accreditation process for researchers and projects. It also discusses the UK Statistics Authority's ethics self-assessment tool and factors that can impact reproducibility when data and code are behind access restrictions in safe havens.
Similar to New Frontiers - Mining the data for our next copper discovery (20)
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Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Sérgio Sacani
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
The cost of acquiring information by natural selectionCarl Bergstrom
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
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New Frontiers - Mining the data for our next copper discovery
1. New frontiers
Mining the data for our
next copper discovery
Copper the the World, June 18th 2019
Holly Bridgwater, Industry Lead
holly@unearthed.solutions
2. We know we need to increase our
discovery rate.
How do we increase our confidence in
the targets we generate?
How do we make the right bet?
6. • The Mount Woods Project is an
area ~ 5000km2 near the
Prominent Hill Mine in South
Australia
• Participants in the competition had
access to the OZ Minerals private
exploration database of >5TB
• The challenge was to use the data
to predict the location of economic
mineralisation of any kind, not just
another Prominent Hill
Crowdsourcing Exploration at Mount Woods
7. What was in the data?
• 621 datasets
• 678 drillholes with 115,000 assay
results
• 2.7TB of geophysics data in 62
datasets
• 60 prospect datasets
• Magnetics, gravity, seismic,
radiometrics, IP, EM and MT
• Petrology
• Geological maps and reports
Crowdsourcing Exploration at Mount Woods
8. The Explorer Challenge
• >5TB of data instantly accessible online
around the world
• >1000 participants
• >10,000 data downloads
• >60 countries
• Geologists, data scientists, startups, students,
consultants, universities, research
organisations
9. The Crowd and Exploration
Open and accessible data creates conditions
for:
• Multiple results to be developed in parallel
• Independent approaches – no group think,
no bias!
• Consensus = Confidence – statistically
relevant consensus due to independence
and diversity
• Speed, new knowledge, new workflows
and << cost are an additional bonus.
11. Explorer Challenge Outcomes
• Multiple approaches never before imagined
internally
• Applications of robust leading edge machine
learning, data science and geological
techniques
• New ways of extracting data, fusing and
analysing multiple data layers
• >400 targets – robust new targets generated,
confidence increased in known targets
12. Data Science and Exploration:
What did we learn?
• Multidisciplinary teams rule!
• DS enables state, national and global
datasets to be trained on and pulled into
local problems, a great way to reduce
bias
• Explainable/interpretable machine
learning is key for it to be added to the
geologists toolkit
• Geoscience data is not friendly for data
scientists
13. The Startup Ecosystem in Exploration Data Science
https://www.linkedin.com/pulse/startups-leveraging-machine-learning-
improve-holly-bridgwater/
14. Key takeaways
• CONSENSUS = CONFIDENCE,
geology is complex: search for
consensus not the best
• Open, accessible data creates an
environment where you can achieve
consensus.
• Data scientists + geologists = success!
• Internal – 1yr, 2-3 models max
• Crowd – 3 months, 40 models