I adopted Mendeley very early and was a defender of their decision to join Elsevier. I didn’t beat them up in the mediasphere for moving from the Open start-up to the publishers corporate mode. I did that myself when ChemSpider was acquired by the Royal Society of Chemistry (RSC is a charity but is also a publisher).
Over the past few weeks I have noticed new followers showing up on my profile. In the first couple of years most of my Mendeley followers were actually names I recognized from my domains of experience of cheminformatics and Nuclear Magnetic Resonance. Most of the followers were scientists whose papers I had read and whose work I was aware of. But things are now different.
I have pasted a picture below of the past month or so of new followers. I don’t recognize any of them at all and as far as I can see they are not from my domain, based on me drilling down into their profile. I cannot figure out whether these are just random followers or not but I guess I should appreciate Mendeley and Elsevier for exposing my work, and publications, to a worldwide community of new followers. I am surprised by the new international exposure! THANKS
Next Tuesday, November 29th, I am leading a two hour workshop as described here:
“The NC-ACS together with RTI International is excited to provide dinner and a workshop titled “Building an Online Profile Using Social Networking and Amplification Tools for Scientists”!
DATE AND TIME: Tue, November 29, 2016, 6:00 PM – 9:00 PM EST
LOCATION: The Frontier, 800 Park Offices Drive, Triangle, NC 27709
The event includes dinner from The Farmery starting at 6PM! The workshop will begin promptly at 6:30PM.
Please note to bring your computer and let our Speaker, Antony Williams, help you build your online profile!
Space is limited! Please register here: https://ncacssocialnetworking.eventbrite.com”
In advance of that gathering I was fortunate to have two papers published last week and I wanted to show how I could use Social Media to drive attention, views, downloads and altmetrics to those papers. They are:
Programmatic conversion of crystal structures into 3D printable files using Jmol at http://dx.doi.org/10.1186/s13321-016-0181-z
An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modelling at http://dx.doi.org/10.1080/1062936x.2016.1253611
I started pushing the 3D printing article out on Friday morning and noticed a surge in attention early in the day and it continued throughout the day. I kept attention going throughout the weekend and saw less attention and while it is possible that I saturated my network of connections I think what is more likely is people are simply away from their computers at the weekend and Twitter will get less attention from the overall network. That’s my hypothesis, yet to be proven. It SHOULD be noted that the initial surge in AltMetrics came from the publisher themselves when they pushed it out for us as authors. See https://twitter.com/jcheminf/status/802078618629373952. I suggest making sure your PUBLISHER is pushing out your article via Twitter as part of their service. And BOOK PUBLISHERS should be using Twitter in the same way.
For the automated curation procedure for data curation and QSAR modeling paper I FOUND that on Friday night about midnight….as I kept checking back to see when it was finally published. (Emails to authors would be a good idea don’t you think?). I pushed that out after midnight on Friday and the attention, and corresponding AltMetrics are way less than for the 3D article. Maybe it’s because the article is less interesting (but I don’t agree with that for my network). Maybe, and more likely I think, is Friday night release and throughout Saturday has less overall Twitter attention (see original hypothesis). But it could be I simply saturated the network with my first 3D printing posting. It’s not possible to tease this out with this one experiment so there will be others. Maybe the study has already been done???
In any case the 3D printing one has good altmetric scores now (40 as of 12:50pm on Sunday) and the QSAR modeling paper is lagging (a score of 4). I think a big contribution to the lagging altmetrics for the QSAR modeling paper is the fact that SAR and QSAR in Environmental Research from Taylor and Francis may not have much of a following and may not tweet out the article directly (the last comments I saw about SAR and QSAR on Twitter were mostly in 2013) . One other MAJOR contributing factor may be that JChemInf is FULLY Open Access and our 3D article is fully Open. The SAR and QSAR article in Taylor and Francis has an Open Access option and we didn’t use it, yet. Again, just hypotheses.
Thanks to @JChemInf for doing their job well re. pushing it out to Twitter.I think it helped….
A new paper that came out of a collaboration initiated at an ACS Meeting, maybe three years ago, has finally gone online. My recollection is that at an ACS CINF reception I started chatting with Vincent Scalfani. At that time I was involved with ChemSpider and he bounced an idea about 3D printing of crystal structures. I reported that we were going to host the Crystal Structures on ChemSpider (here) and Vincent even presented on it at the ACS (here, with >2000 views). But as happened on a fairly regular basis a great idea never came to fruition and the data were not put onto ChemSpider, and I left to join the EPA over eighteen months ago.
But it was still great work, and when it was made clear that the data would not see light of day the original article, written 2 years ago give or take, was adjusted to simply communicate that the data were available on Figshare here (https://dx.doi.org/10.6084/m9.figshare.c.3302859.v6). The peer review process gave good feedback and pretty much said “Why aren’t they on a searchable database”? Well, we tried, but Bob Hanson, JMol-hero, got to work and produced this site in a few days! Bob is incredibly productive.
Well then the paper was accepted, all is good, the data are open and the world has access to tens of thousands of crystal structures ready for printing.
The paper is available here: “Programmatic conversion of crystal structures into 3D printable files using Jmol” at http://jcheminf.springeropen.com/articles/10.1186/s13321-016-0181-z
I have always been impressed with Google Scholar Citations. When I first set up my profile I was impressed with how fast the site allowed me to set up my profile (available at https://scholar.google.com/citations?user=OQEPQAAAAJ) and the overall accuracy that was evident in terms of recognizing the articles I had authored or co-authored. There was very little noise in terms of associating articles for “Antony Williams, Anthony Williams or A.J. WIlliams” (or some other combination) with my profile that were not actually my articles. As I recall maybe 3 articles overall out of about 120 at the time. I did have to add a couple of publications that were missed but these were old, from the late 1980s.
Over the years I have been kept informed of publications that have been of relevance to my work and definitely of interest. I have also been made aware of citations to my work via email. Overall, it’s a great service.
However, of late I have become increasingly concerned regarding data quality. I have started to notice suggested co-authors showing up on my profile and emails regarding citing articles that puzzle me.
For example, today on my profile I notice the following list of suggested co-authors. Four of these are blocked in red and I have no recollection of authoring with. It is possible that these people are editors of a book that I have a chapter in but not that I recall.
I have rarely had to remove many associations with my profile that were incorrect but something is afoot methinks. I ended up deleting a grand total of over SEVENTY mis-associations. Some examples are below. To clarify, I know how to sleep but don’t study sleep disorders and breathing.
I eat cream cheese but know nothing about cheese manufacture
and I don’t know much about energy demands in Western Europe.
These articles have shown up on my profile only of late (as far as I know) and it seems that Google is casting a wider net to map more works to my profile but the dramatic DECREASE in data quality is very concerning. Whatever the decision was to do this I think it has backfired. How badly?? See below where publications are associated with my profile…that I somehow authored before I was born! I was born in 1964 so how did the 1953 article get associated with me?
The BOOK by Anna Williams from 1766 from can be purchased on eBay for less than $1000 if you want it. However, it wasn’t written by Antony Williams and should NOT be associated with my profile.
Hopefully someone associated with Google Scholar Citations sees this as input to revisit any recent changes in algorithms for associating publications with profiles.
By the way, I did take a hit, appropriately so, on my h-index when I deleted the 70 mis-associations with my name. They weren’t mine for sure!
This presentation will be given at the Janelia Farm Research Campus, a research campus of the Howard Hughes Medical Institute. The presentation abstract is below.
Despite the availability of many platforms for scientists to connect and share with their peers in the scientific community the majority do not make use of these tools, despite their promise and potential impact and influence on our careers. We are already being indexed and exposed on the internet via our publications, presentations and data and new “AltMetric scores” are being assigned to scientific publications as measures of popularity and, supposedly, of impact. We now have even more ways to contribute to science, to annotate and curate data, to “publish” in new ways, and many of these activities are as part of a growing crowdsourcing network. This presentation provides an overview of the various types of networking and collaborative sites available to scientists and ways to expose your scientific activities online. It will discuss the new world of AltMetrics that is in an explosive growth curve and will help you understand how to influence and leverage some of these new measures. Participating online, whether it be simply for career advancement or for wider exposure of your research, there are now a series of web applications that can provide a great opportunity to develop a scientific profile within the community.
This presentation was given at the ACS Meeting in Philadelphia in August 2016.
Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much-reduced cost relative to historical approaches. This work involves computational and data-driven approaches including high-throughput screening, modeling, text mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data
Presentation given at ACS Meeting in Philadelphia in August 2016
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data
There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.
Last night I was honored to receive an award from the North Carolina Local Section of the American Chemical Society. I had the chance to review the past 20 years of my career with the attendees. I assembled a slide deck from about ten years of slides stored on Slideshare (I am glad I have been storing them there as it’s a great online storage place!). I appreciate the recognition from the Local Division. THANKS!
Call For Papers: Applications of Cheminformatics and Computational Chemistry in Environmental Health
CALL FOR PAPERS
Applications of Cheminformatics and Computational Chemistry in
253rd American Chemical Society National Meeting & Exposition
“Advanced Materials, Technologies, Systems & Processes”
San Francisco, California, April 2-6, 2017
Abstract Deadline: October 2016
Cheminformatics and computational chemistry have had an enormous impact in regards to providing environmental chemists and toxicologists access to data, information and knowledge. With an overwhelming array of online resources and an increasingly rich collection of software tools, the ability to source information continues to expand. Scientists typically seek chemical data in the form of chemical properties, their function and use, as well as information regarding their exposure potential, persistence in the environment and their transformation in environmental and biological systems. Commonly, the most pressing concern regarding chemicals is their potential as environmental toxicants. The increasing rate of production and release of new chemicals into commerce requires improved access to historical data and information to assist in hazard and risk assessment. High-throughput in vitro and in silico analyses increasingly are being brought to bear to rapidly screen chemicals for their potential impacts and interweaving this information with more traditional in vivo toxicity data and exposure estimation to provide integrated insight into chemical risk is a burgeoning frontier on the cusp of cheminformatics and environmental sciences.
This symposium will bring together a series of talks to provide an overview of the present state of data, tools, databases and approaches available to environmental chemists. The session will include the various modeling approaches and platforms, will examine the issues of data quality and curation, and intends to provide the attendees with details regarding availability, utility and applications of these systems. We will focus especially on the availability of Open systems, data and code to ensure no limitations to access and reuse.
The topics that would be covered in this session are, but are not limited to:
Please submit your abstracts using the ACS Meeting Abstracts Programming System (MAPS) at https://maps.acs.org. General information about the conference can be found at www.acs.org/meetings. Any other inquiries should be directed to the symposium organizers:
Antony J. Williams and Chris Grulke, National Center for Computational Toxicology, Environmental Protection Agency, Research Triangle Park, Durham, NC