Website of the month for August - Altmetric Bookmarklet for Researchers

Not so much a website this month but a snazzy little plug in for researchers and librarians among other research professionals that helps you find out how much attention a research publication has received. This little tool has been around for quite a while and is simple to use and can provide insights on whether your paper has been mentioned in the media, in Wikipedia or across social media platforms like Twitter.

You can obtain the web extension for Chrome, Firefox and Safari here 

https://www.altmetric.com/products/free-tools/bookmarklet/

More information from Altmetric.com

• The Bookmarklet only works on PubMed, arXiv or pages containing a DOI with Google Scholar friendly citation metadata
• Twitter mentions are only available for articles published since July 2011
• You can request support for a particular journal by asking @altmetric for it on Twitter
• Are you a publisher? Don’t use this bookmarklet! We have much better tools for you, just get in touch.

Website of the Month - The Human Mortality Database

Each month we highlight a website, database or toolkit that we think would be of use to readers of our blog. This month we've selected The Human Mortality Database. It's particularly apt given the current global situation that they have created a new data resource: Short-term Mortality Fluctuations (STMF) data series.  

Here's more information form their website:

'Objective and internationally comparable data are crucial to determine the effectiveness of different strategies used to address epidemics. Weekly death counts provide the most objective and comparable way of assessing the scale of short-term mortality elevations across countries and time. We provide weekly death counts for 25 countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Belgium, England and Wales, Estonia, Finland, France, Germany, Hungary, Iceland, Israel, Italy, Lithuania, Luxembourg, Netherlands, Norway, Portugal, Scotland, Slovakia, Spain, Sweden, Switzerland and the USA. The same data in the pooled CSV file are available for download. Data formats and methods are described in the STMFNote. We also strongly recommend reading the metadata text. Following the HMD practice, we also publish original input data in standardized format. During the next few weeks data will be frequently updated and new countries will be added. The most recent STMF update is: 2020-07-08." 

"New: We invite you to explore this data with our online STMF visualization toolkit."

More information about The Human Mortality Database. "The Human Mortality Datbase (HMD) was created to provide detailed mortality and population data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity. The project began as an outgrowth of earlier projects in the Department of Demography at the University of California, Berkeley, USA, and at the Max Planck Institute for Demographic Research in Rostock, Germany"

https://www.mortality.org/

Website of the Month for June - Aerialod

Every month we like to highlight a useful website, dataset or app that we think readers of this blog will find useful. This month we deviate from the path a little, following a stream of engaging Tweets by our own Colin Angus. Colin is an alcohol policy modeller in HEDS and has increasingly been expanding his modelling skills portfolio using a set of tools and data to model everything from his alcohol research to places he has climbed. If you follow Colin on Twitter you'll see a stream of eye catching models and visualisations, with many looking at the impact of COVID in various communities up and down the UK. His inspiration to carry out this work came from another Sheffield colleague, Professor Alasdair Rae from the Department of Urban Studies and Planning. Alasdair wrote a blog article earlier this year that explains how to visualise 3D landscapes and cities using a piece of free software called Aerialod. The original post is below and was published under a Creative Commons licence - many thanks to Alasdair for sharing.

http://www.statsmapsnpix.com/2019/11/amazing-3d-rendering-with-aerialod.html

Making 3D landscape and city models with Aerialod

This is my second post on Aerialod - the interactive path tracing 

renderer for height maps, by @ephtracy. It's available in 32 and 

64-bit versions on Windows and it's super-lightweight but you can

 do some really amazing things with it. My previous post covers 

more of the basics, including controls and interface settings, so 

here I'll share some more information on how to tweak the settings

 (of which there are many) to create nice looking vistas. But as a 

quick reminder, hold down your right mouse button to rotate the 

map and use the space bar plus the left mouse button to move it 

around. Scroll wheel to zoom in and out. Keyboard shortcuts are 

here.

First I'll show you some new visuals I created in Aerialod, then I'll 

show you some of the settings I used to create them - in 

screenshots and in a small slide set. All the images I've posted

below are in a shared folder, as well as a sample Lidar dataset for Cheddar Gorge in England that you can just drop in to Aerialod and

then tweak the settings as you wish. You can of course create these 

kinds of images in other software (notably Blender) but Aerialod

 is much easier to use, though can be confusing at first.
So, let's begin with the highest peaks in Scotland, England and

Wales, plus one other view that I like.

I did this using a 5m DTM (not open data)

See the curved horizon? - that's the SG lens setting

A very nice looking mountain

I've added Glen Etive because it's so lovely

But of course we don't always have to map things like mountains. If we have good quality Lidar data, as we do in much of the UK, we can create quite interesting cityscapes, as you can see below.

Here's a little Salford Sunset to get things rolling

A Newcastle-Gateshead vista, along the Tyne

The example data I've put in the shared folder is of Cheddar Gorge in the south west of England, and it looks like this once you fiddle with a few settings.

Sun low in the sky, dusky effect

I've tweaked some of the settings here to make it glow

Different angle, light filtering through the gorge

A foggier, early morning effect

So how do you do all this?
If you've not used Aerialod before then you'll really need to read my first blog post on it in order to get to grips with the controls, etc. Once you've done this, look closely at the screenshots below as the settings in them show you how I achieved the effects in the four images above. Study them closely and then see further below for a short slide set with more annotation on the settings options in Aerialod.

Take some time to Google some of the different terms and they'll begin to make a lot more sense - e.g. the Rayleigh setting refers to Rayleigh scattering, which relates to the blue colour we see in the sky. So, using the default Rayleigh setting in Aerialod you'll see a blue sky but if you reduce the number to, say 10, it will become more blue and if you put it up to 90, for example, it will look a lot less blue and instead more like a lovely glowing orange/yellow sunset. 

This relates to the first Cheddar Gorge image

This also relates to the first image

Notice the glowing light at the corners here

This is the fourth Cheddar Gorge image above

In addition to reading this, it's a good idea to check out the @ephtracy Twitter account for other tips, plus the #aerialod hashtag on Twitter. There are also now a few good video tutorials online, including this one by Steven Scott.

Here is the small set of slides, with annotated screenshots, that I made in order to help you get to grips with the settings a little better - direct link here.

All this, including the data, can be found in the Aerialod tutorial folder I made for this short blog post. Just drag and drop the .asc file I provided into Aerialod and start playing around.

I've put everything in here

The information above should be all you need to create more realistic, impressive 3D landscape or city models. It all depends of course upon being able to get good quality data at a high resolution - I've provided an example in the folder, but you can get a lot more on the Defra Lidar download page for England. You can use the OpenDem searcher to find suitable data for other parts of the world.

To end, I'm just going to post a few more images that I haven't shared anywhere else before, before a few final comments.

This is done by keeping the 'Map' option on in Grid settings

In the example above, I have all the options on in the Grid settings (Map, Ground, Vertical) and then I have used a value in the 'Step' settings on the right to match the resolution of the underlying data (in this case 5 metres) so that I get a blocky kind of effect - see below.

This works if you want to Minecraft your map

The Western Highlands of Scotland

In the image above, I just used a 1:50,000 Land-Form dataset shared by Carol Blackwood to render the Western Highlands of Scotland - I added the labels using GIMP. You can get the individual tiles as open data from Ordnance Survey as well (OS Terrain 50).

This city is home to two football teams, as you can see here

In the example above, I've just taken some Lidar open data of Liverpool and created a view looking down on Anfield and Goodison - home to Liverpool and Everton respectively. They are very close together and the densely packed terraced housing nearby also makes for an interesting example use case with this kind of data.

And, last but not least, St Kilda - a very wild and remote archipelago off the Western Isles of Scotland that is now a World Heritage Site.

In this example, I've added some fog

Notes: you can add a single file to Aerialod (it can handle PNG, JPG, TIF, IMG and ASC formats) or you can add multiple files at once using the little button on the top right that looks like a folder. That is covered in my previous blog post. If you try to load humongous bytes of data then it may crash. Sometimes it won't crash but just won't load. Generally I find it just works and the Scotland 1:50,000 terrain model above is over 600MB and worked fine for me. Just remember that when you hover over any of the tools in Aerialod you will get information on what it is and what it does at the bottom of the window. 

Citation: Blackwood, Carol. (2017). Scotland Land-Form PANORAMA® DTM, [Dataset]. EDINA. https://doi.org/10.7488/ds/1929.

HEDS website of the month for May - MetaInsight and MetaDTA

Every month we like to share a useful website or resource we have come across on our travels across the research web. This month we have a couple of really useful free-to-use online apps that have been developed for evidence synthesis by the Complex Review Support Unit (http://www.nihrcrsu.org/). 

These were initially aimed at non-statistical experts to assist with the conduct of the analysis required for systematic reviews, but we have had comments from statisticians that their user-friendliness makes them helpful tools for all.

The first is MetaInsight https://crsu.shinyapps.io/metainsight_continuous2/  which conducts network meta-analysis using both frequentist and Bayesian approaches.

MetaInsight

The second is MetaDTA https://crsu.shinyapps.io/dta_ma/ which conducts meta-analysis of diagnostic test accuracy studies.

https://crsu.shinyapps.io/dta_ma/

Finally, a special version of MetaInsight – MetaInsight : COVID-19 has been released https://crsu.shinyapps.io/metainsightcovid/. This is a specially tailored version of the network meta-analysis app built around the trial evidence on pharmacological treatments for COVID-19. They are collecting the data from a pre-existing living systematic review https://covid-nma.com/ and their aim is to regularly update the data as trial results are made available. The intention of the app is to allow the interested user to dig deeper into the data and explore how changes to inclusion criteria and model choice etc impact on the findings. (There is not much data at present, but they anticipate this will change quickly)

HEDS Website of the month for April - COVID19 Data Portal

This month's website of the month will hopefully prove incredibly useful for those involved in the work going on to fight COVID19 

https://www.covid19dataportal.org/

The COVID19 Data Portal says: The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.

https://www.covid19dataportal.org/

More information taken from the COVID19 Data Portal

The aim of the COVID-19 Data Portal is to facilitate data sharing and analysis, and to accelerate coronavirus research

An unprecedented number of scientific efforts are taking place worldwide in order to help combat the new coronavirus epidemic (COVID-19). One of the biggest challenges in this fast-moving situation is to share data and findings in a coordinated way, in order to understand the disease and to develop treatments and vaccines.

To address this challenge, EMBL-EBI and partners have has set up the COVID-19 Data Portal, which will bring together relevant datasets submitted to EMBL-EBI and other major centres for biomedical data. The aim is to facilitate data sharing and analysis, and to accelerate coronavirus research.

The COVID-19 Data Portal will enable researchers to upload, access and analyse COVID-19 related reference data and specialist datasets.

The COVID-19 Data Portal will be the primary entry point into the functions of a wider project, the European COVID-19 Data Platform.

Rapid and open sharing of data greatly accelerates research and discovery, which is essential to respond to the COVID-19 pandemic. The European Commission and EMBL’s European Bioinformatics Institute (EMBL-EBI), together with EU Member States and research partners such as ELIXIR, are deploying a dedicated European COVID-19 Data Platform that will enable the rapid collection and comprehensive data sharing of available research data from different sources for the European and global research communities. This joint effort is a priority pilot to realise the objectives of the European Open Science Cloud (EOSC).

The European COVID-19 Data Platform will consist of two connected components:

• SARS-CoV-2 Data Hubs, which will organise the flow of SARS-CoV-2 outbreak sequence data and provide comprehensive open data sharing for the European and global research communities.
  Read more about the Data Hubs >
• COVID-19 Data Portal, which will bring together and continuously update relevant COVID-19 datasets and tools, will host sequence data sharing and will facilitate access to other SARS-CoV-2 resources.

Website of the month for February - Top Factor

For February's website of the month we cast our view to perhaps the future of how academic journals might be evaluated and a new metric - The Top Factor. This is a project by the Center for Open Science and stands for Transparency and Openness Promotion and looks to highlight which journals meet transparency and reproducibility standards.

https://topfactor.org/

Taken from the Top Factor website

The Standards

Published in Science in 2015 (OA), the Transparency and Openness Promotion Guidelines (PDF and HTML) include eight modular standards, each with three levels of increasing stringency. Journals select which of the eight transparency standards they wish to implement and select a level of implementation for each. These features provide flexibility for adoption depending on disciplinary variation, but simultaneously establish community standards.

Standards: Data Citation | Data, Materials, and Code Transparency | Design and Analysis | Preregistration | Replication

Levels: Disclose, Require, or Verify

TOP Factor

Journal policies can be evaluated based on the degree to which they comply with the TOP Guidelines. This TOP Factor is a metric that reports the steps that a journal is taking to implement open science practices, practices that are based on the core principles of the scientific community.  It is an alternative way to assess journal qualities, and is an improvement over traditional metrics that measure mean citation rates. The TOP Factor is transparent (see underlying data and the evaluation rubric) and will be responsive to community feedback.

Read more about TOP Factor here.