about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Amanuens.is HUmans and machines annotating scholarly literature TheContentMine
Published on May 19, 2016 by PMR
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Automatic Extraction of Knowledge from Biomedical literaturepetermurrayrust
a plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
High throughput mining of the scholarly literature TheContentMine
Published on Jun 7, 2016 by PMR
Talk given to statisticians in Tilburg, with emphasis on scholarly comms for detecting unusual features. Includes demo of Amanuens.is and image mining
Automatic Extraction of Knowledge from Biomedical literature TheContentMine
Published on Mar 16, 2016 by PMR
A plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Amanuens.is HUmans and machines annotating scholarly literature TheContentMine
Published on May 19, 2016 by PMR
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Automatic Extraction of Knowledge from Biomedical literaturepetermurrayrust
a plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
High throughput mining of the scholarly literature TheContentMine
Published on Jun 7, 2016 by PMR
Talk given to statisticians in Tilburg, with emphasis on scholarly comms for detecting unusual features. Includes demo of Amanuens.is and image mining
Automatic Extraction of Knowledge from Biomedical literature TheContentMine
Published on Mar 16, 2016 by PMR
A plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Automatic Extraction of Knowledge from the Literaturepetermurrayrust
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Liberating facts from the scientific literature - Jisc Digifest 2016 TheContentMine
Published on Mar 4, 2016 by PMR
Text and data mining (TDM) techniques can be applied to a wide range of materials, from published research papers, books and theses, to cultural heritage materials, digitised collections, administrative and management reports and documentation, etc. Use cases include academic research, resource discovery and business intelligence.
This workshop will show the value and benefits of TDM techniques and demonstrate how ContentMine aims to liberate 100,000,000 facts from the scientific literature, and ContentMine will provide a hands on demo on a topical and accessible scientific/medical subject.
Can Computers understand the scientific literature (includes compscie material)TheContentMine
Published on Jan 24, 2014 by PMR
With the semantic web machines can autonomously carry out many knowledge-based tasks as well as humans. The main problems are not technical but the prevention of access to information. I advocate automatic downloading and indexing of all scientific information
Mining the scientific literature for plants and chemistrypetermurrayrust
ContentMine can read the daily scientific literature and extract facts. This talk was given to the OpenPlant project - with whom ContentMine collaborate at a meeting on 2016-07-25/27 in Norwich. Examples of extracted facts are given.
Published on Jan 29, 2016 by PMR
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuous Integration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of content mining (TDM)
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus.
Three slides have embedded movies - these do not show in slideshare and a first pass of this can be seen as a single file at https://vimeo.com/154705161
Automatic Extraction of Science and Medicine from the scholarly literaturepetermurrayrust
Many scientists have to extract many facts out the scholarly literature - to evaluate other work or to extract useful collections of facts. This shows the approach, especially for systematic reviews of animal or clinical trials
Talk to OpenForum Academy (Open Forum Europe) about Text and data Mining. Four use cases selected fo non-scientists. Also discussion of latest on Europena copyright reform and TDM exceptions
Published on Feb 07, 2016 by PMR
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus. Includes clips of the software in action
Published on Feb 29, 2016 by PMR
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Can machines understand the scientific literaturepetermurrayrust
With over 5000 scientific articles per day we need machines to help us understand the content. This material is to be used at an interactive session for the Science Society at Trinity College Cambridge UK
Asking the scientific literature to tell us about metabolismpetermurrayrust
Talk to Lhasa Ltd (a world leader in predicting drug metabolism and toxicity. Uses the scientific literature to answer questions on metabolism, chemical transformation. Almost all of the data in a paper can be queried.
Automatic Extraction of Knowledge from the Literaturepetermurrayrust
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Liberating facts from the scientific literature - Jisc Digifest 2016 TheContentMine
Published on Mar 4, 2016 by PMR
Text and data mining (TDM) techniques can be applied to a wide range of materials, from published research papers, books and theses, to cultural heritage materials, digitised collections, administrative and management reports and documentation, etc. Use cases include academic research, resource discovery and business intelligence.
This workshop will show the value and benefits of TDM techniques and demonstrate how ContentMine aims to liberate 100,000,000 facts from the scientific literature, and ContentMine will provide a hands on demo on a topical and accessible scientific/medical subject.
Can Computers understand the scientific literature (includes compscie material)TheContentMine
Published on Jan 24, 2014 by PMR
With the semantic web machines can autonomously carry out many knowledge-based tasks as well as humans. The main problems are not technical but the prevention of access to information. I advocate automatic downloading and indexing of all scientific information
Mining the scientific literature for plants and chemistrypetermurrayrust
ContentMine can read the daily scientific literature and extract facts. This talk was given to the OpenPlant project - with whom ContentMine collaborate at a meeting on 2016-07-25/27 in Norwich. Examples of extracted facts are given.
Published on Jan 29, 2016 by PMR
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuous Integration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of content mining (TDM)
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus.
Three slides have embedded movies - these do not show in slideshare and a first pass of this can be seen as a single file at https://vimeo.com/154705161
Automatic Extraction of Science and Medicine from the scholarly literaturepetermurrayrust
Many scientists have to extract many facts out the scholarly literature - to evaluate other work or to extract useful collections of facts. This shows the approach, especially for systematic reviews of animal or clinical trials
Talk to OpenForum Academy (Open Forum Europe) about Text and data Mining. Four use cases selected fo non-scientists. Also discussion of latest on Europena copyright reform and TDM exceptions
Published on Feb 07, 2016 by PMR
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus. Includes clips of the software in action
Published on Feb 29, 2016 by PMR
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Can machines understand the scientific literaturepetermurrayrust
With over 5000 scientific articles per day we need machines to help us understand the content. This material is to be used at an interactive session for the Science Society at Trinity College Cambridge UK
Asking the scientific literature to tell us about metabolismpetermurrayrust
Talk to Lhasa Ltd (a world leader in predicting drug metabolism and toxicity. Uses the scientific literature to answer questions on metabolism, chemical transformation. Almost all of the data in a paper can be queried.
Architecture of ContentMine Components contentmine.orgpetermurrayrust
This is the evolving architecture of ContentMine (contentmine.org) architecture. It includes an overview ( slide #2, ) showing getpapers, quickscrape, norma and ami.
The key container is the CTree and the architecture shows where components are added or transformed to this.
These slides are dated and may be out-of-date wrt code. Some diagrams are autogenerated from *.dot files.
Please use http://discuss.contentmine.org/c/software as the main source of up-to-date info. Feel free to ask questions, offer help, critique, etc.
All s/w is Open (BSD, Apache2)
ContentMining for France and Europe; Lessons from 2 years in UKpetermurrayrust
I have spend 2 years carrying out Content Mining (aka Text and Data Mining) in the UK under the 2014 "Hargreaves" exception. This talk was given in Paris, to ADBU , after France had passed the law of the numeric Republique. I illustrate what worked in what did not and why and offer ideas to France and Europe
Asking the scientific literature to tell us about metabolismpetermurrayrust
Talk at Lhasa (https://www.lhasalimited.org/) a leading organization for "in silico prediction and database systems for use in metabolism, toxicology and related sciences". ContentMine software can extract data from papers on compound metabolism in reusable semantic form, including metabolic pathways, pharmacokinetic data.
We have developed image processing techniques to extract data from diagrams used in science and scientific publications. These slides were presented at a workshop session for the Cambridge MPhil in Computational biology. There is an overview of the main techniques for cleaning diagrams, such as thresholding, binarization, edge detection and thinning. Examples are given from plots, phylogenetic trees, chemistry and neuroscience spikes. All software is Open Source and most is Java
Early Career Reseachers in Science. Start Early, Be Open , Be Bravepetermurrayrust
Highlights the importance of supporting Early Career Researchers to pursue their own ideas, possibly alongside their main research. Illustrated with biology but applies to all fields of science. This was a 14 min presentation and shows narratives of how ECRs develop and reinforce each other.
The Publisher -Academic complex is a dystopian cycle where academia gives (mega)publishers manuscripts, reviews and money and the publishers give personal and institutional glory(vanity). This is analysed in its origins, impact and harm. The disruption can come from Advocacy/Activism, Community and Tools. Disruption comes from doing things Better or Novel, not Prices
AUDIO : https://soundcloud.com/damahub/peter-murray-rust-disturbing-the-publisher-academic-complex-210418-british-library
Thanks to DaMaHub
This has now been edited by Ewan McAndrew (Edinburgh Wikimedian in Residence) many thanks - to synchronize the slides with the soundtrack. https://media.ed.ac.uk/media/1_46h85ltt Brilliant
The scientific scholarly literature now contains many millions of articles. The contain semi-structured information of high quality and veracity. We show how this resource can be converted to a universal Wikicite format and full-text indexed against Wikidata dictionaries. We now have > 5 million bibliographic records and over 200 dictionaries based in Wikidata properties and queriable by SPARQL.
The ContentMine system (Open Source) can search EuropePMC and download hundreds of articles in seconds. These can be indexed by AMI dictionaries allowing a rapid evaluations and refinement of the search
Presentation given at NUI, Galway 2019-04-11 for Open Science Week.
An overview of Early Career Researchers, their innovation and contribution towards Open Infrastructure
Paradise Lost and The Right to Read is the Right to Minepetermurrayrust
Presented to UIUC CIRSS seminars to a mixed group of Library, CS, domain scientists with a great contingent of Early Career Researchers. Starts by honouring the creation of the wonderful NCSA Mosaic at UIUC in 1993 and the paradise of knowledge and community it opened. Then shows the gradual and tragic decline of the web into a megacorporate neocolonialist empire, where knowledge is sacrificed for money and power.
You have seen many of the slides before but the words are different and have been recorded.
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Published on May 18, 2015 by PMR
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuousIntegration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of contentmining (TDM)
The Culture of Research Data, by Peter Murray-RustLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Peter Murray-Rust, ContentMine.org and University of Cambridge
Automatic Extraction of Science and Medicine from the scholarly literatureTheContentMine
Published on Jun 04, 2015 by PMR
Many scientists have to extract many facts out the scholarly literature - to evaluate other work or to extract useful collections of facts. This shows the approach, especially for systematic reviews of animal or clinical trials
ContentMine: Open Data and Social MachinesTheContentMine
Published on Nov 13, 2014 by PMR
Scientific information is often hidden or not published properly. The ContentMine is a Social Machine consisting of semantic software and communities of domain expertise; it aims to liberate all scientific facts from the published literature on a daily basis.
The talk , delivered to the Computational Institute, will be /was followed by a hands-on workshop learning how to use the technology and work as a community.
Liberating facts from the scientific literature - Jisc Digifest 2016Jisc
Text and data mining (TDM) techniques can be applied to a wide range of materials, from published research papers, books and theses, to cultural heritage materials, digitised collections, administrative and management reports and documentation, etc. Use cases include academic research, resource discovery and business intelligence.
This workshop will show the value and benefits of TDM techniques and demonstrate how ContentMine aims to liberate 100,000,000 facts from the scientific literature, and ContentMine will provide a hands on demo on a topical and accessible scientific/medical subject.
Can machines understand the scientific literature?petermurrayrust
A presentation to Cambridge MPhil Computational Biology. 2020-11-11 . Presenters Peter Murray-Rust, Shweata Hegde and Ambreen Hamadani from https://github.com/petermr/openvirus .
This chunk is PMR with a large break in the middle for SH and AH talks.
I cover Global Challenges, knowledge equity, semantics of scientific articles, Wikidata, Data Extraction from images, and ethics/politics.
Answer: Yes, technically. No, politically as the Publisher-Academic Complex will block it.
Semantic content created from Open Access papers to help in the fight against viral epidemics. Includes contributions from NIPGR interns, 5 supported by Indian National Young Academy of Scientists.
Overview of openVirus project. Interns in India have worked for 2 months to extract scientific knowledge from the literature about viral epidemics. Covers data science, machine learning and virtual collaboration
Automatic mining of data from materials science literaturepetermurrayrust
The literature on materials science (batteries, etc.) contains huge amounts of scientific facts, but not in easily accessible form. our AMI program has been developed to automatically:
scrape , clean, annotate and display/publish
data for re-use in science.
Examples will be given from electrochemistry, magnetism and other fields . The general principles and (open) tech are applicable to many other disciplines.
A presentation by Open Climate Knowledge for European Forum for Advanced Practices. Showing how the scientific literature can be searched for knowledge on this multidisciplinary topic.
XML for science; its huge potential; but are pubiishers preventing it?petermurrayrust
XML can represent almost all well derfined scientific objects. chemistry, plants medcine. But it's not yet widely used. Is this because publishers oppose thr re-use of science?
The scientific and medical literature is a vast resource of knowledge, but it needs turning into semantic FAIR form. The ContentMine can do this and we presented a rapid overview of the potential
A 10-minute talk to lovers of early science (e.g. 1600-1900) at the Royal Society. Archivists , computer vision, scientific historical metadata all relevant.
I chose 4 examples of monochrome diagrams that I can extract something from automatically. Some of the methids would scale to larger volumes , e.g. tables for figures, or maps with points
WikiFactMine: Ontology for Everybody and Everythingpetermurrayrust
WikiFactMine https://www.wikidata.org/wiki/Wikidata:WikiFactMine consists of several hundreds dictionaries created from Wikidata. They cover everything from science to medicine to geo to arts. Every item has a unique identifier (Q) and normally has several properties (P) creating a series of triples. Using SPARQL it's possible to create sophiticated queries and run them in seconds
ContentMining (aka Text and Data Mining TDM) is beneficial, legal in the UK and a few other countries. Many groups in Europe are looking to make it legal there as well but there are many vested interests who oppose it.
This short presentation shows the benefits of content mining, some of the technology, and the way that it can be used and promotedby communities of practice. I urge all attendees at CopyCamp and also the wider world to press for liberalization of Copyright
The mining "Revolution"; are Libraries supporting Researchers or Publishers"?petermurrayrust
increasingly we find that mega-corporations have taken control over scholarship. We could use the scholarly literature as a knowledge resource but megacorps try to stop this - and often libraries support them rather than researchers.
WikiFactMine uses dictionaries created directly from Wikidata to search the scientific literature. The example given is for papers which contain mention of conifers and terpenes (volatile plant organic compounds). Traditional queries and content are expanded by the system to be much broader and more precise than traditional keyword searchers of abstract
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
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.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
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.
Multi-source connectivity as the driver of solar wind variability in the heli...
Amanuens.is HUmans and machines annotating scholarly literature
1. Amanuens.is
ContentMine
IAnnotate!, Berlin, DE, 2016-
05-18
Peter Murray-Rust
[1]University of Cambridge [2]TheContentMine
ContentMine + Hypothesis annotate the scientific literature!
100, 000 + per day.
Live demos!
2. Scholarly publishing
• 10, 000 articles per day
• 20 Billion USD / year [1]
• Totally and scandalously broken. Primary revenue
comes from throttling the flow of knowledge
• Massive disruption likely (Sci-Hub)
• Mining and annotation liberation tools.
[1] (2x digital music industry!)
4. • Science can be read and understood by
human-machine Amanuensis-symbionts.
• Amanuenses based on Wikipedia Wikidata,
software (ContentMine’s AMI)
• Results are fed back into WP and WikiData
• Annotation through Hypothes.is
http://en.wikipedia.org/wiki/Symbiosishttp://en.wikipedia.org/wiki/Eric_Fenby
5. What plants produce Carvone?
https://en.wikipedia.org/wiki/Carvone
https://en.wikipedia.org/wiki/Carvone
16. Annotation sent to hypothes.is
prefix
suffix
source
user
text
uri
maybe 100+ annotations per paper
text
17. @Senficon (Julia Reda) :Text & Data mining in times of
#copyright maximalism:
"Elsevier stopped me doing my research"
http://onsnetwork.org/chartgerink/2015/11/16/elsevi
er-stopped-me-doing-my-research/ … #opencon #TDM
Elsevier stopped me doing my research
Chris Hartgerink
18. I am a statistician interested in detecting potentially problematic research such as data fabrication,
which results in unreliable findings and can harm policy-making, confound funding decisions, and
hampers research progress.
To this end, I am content mining results reported in the psychology literature. Content mining the
literature is a valuable avenue of investigating research questions with innovative methods. For
example, our research group has written an automated program to mine research papers for errors in
the reported results and found that 1/8 papers (of 30,000) contains at least one result that could
directly influence the substantive conclusion [1].
In new research, I am trying to extract test results, figures, tables, and other information reported in
papers throughout the majority of the psychology literature. As such, I need the research papers
published in psychology that I can mine for these data. To this end, I started ‘bulk’ downloading research
papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account
potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention
to redistribute the downloaded materials, had legal access to them because my university pays a
subscription, and I only wanted to extract facts from these papers.
Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days.
This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day.
Approximately two weeks after I started downloading psychology research papers, Elsevier notified my
university that this was a violation of the access contract, that this could be considered stealing of
content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading
(which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university.
I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly
hampering me in my research.
[1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The
prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods, 1–22.
doi: 10.3758/s13428-015-0664-2
Chris Hartgerink’s blog post
![Amanuens.is
ContentMine
IAnnotate!, Berlin, DE, 2016-
05-18
Peter Murray-Rust
[1]University of Cambridge [2]TheContentMine
ContentMine + Hypothesis annotate the scientific literature!
100, 000 + per day.
Live demos!](https://image.slidesharecdn.com/amanuens-160519120633/85/Amanuens-is-HUmans-and-machines-annotating-scholarly-literature-1-320.jpg)
![Scholarly publishing
• 10, 000 articles per day
• 20 Billion USD / year [1]
• Totally and scandalously broken. Primary revenue
comes from throttling the flow of knowledge
• Massive disruption likely (Sci-Hub)
• Mining and annotation liberation tools.
[1] (2x digital music industry!)](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)