This post was originally written for and published on the University of Manchester Library’s Research Plus blog here.
I applied to attend OpenCon 2017 to be inspired by and network with other pioneers of the Open Movement. There were thousands of applicants for this year’s event from over 175 countries, but there were only a few hundred places at the conference to represent our global community. I was wait-listed to attend based on my main application (which you can read on my GitHub here along with the response from the OpenCon 2017 Organising Committee). This was pretty good considering the odds, but I was still gutted. However, I was lucky enough to see that the University of Manchester Library was holding a competition to sponsor a student or staff member to attend. I therefore remixed my main application to answer the University of Manchester-specific questions (which you can read on my GitHub here) and submitted it to the competition. I was very happy when it was announced that I won the sponsored place! Continue reading “OpenCon 2017”→
The argument for better data practice is made stronger by global concerns about reproducibility and research integrity, reducing fraud and improving patient outcomes.
The case for good research practice and open data to research outputs is increasingly inarguable. Open access to research data can help speed the pace of advancing discovery and deliver more value by enabling reuse and reducing duplication. Good data practice also makes research more efficient, effective and fulfilling for researchers. As the data in this survey show, the research community recognize the value of open data, yet good data practice and data sharing are still far from the status quo.
Springer Nature and its publications have been advocating for good data practice for over a decade. Recent efforts have focussed on growing data publishing options to provide credit, and strengthening and simplifying our data policies. Our future focus is on support and incentives to enable data sharing, data management and open data, built in collaboration with the research community.
The case for data
The argument for better data practice is made stronger by global concerns about reproducibility and research integrity, reducing fraud and improving patient outcomes. As much as 50% of preclinical research done in the US, at a cost of US$56.4B a year, cannot be reproduced, estimates a 2015 study In the same year, a Nature survey found that 70% of over 1,500 respondents had tried and failed to replicate the work of others. More shocking was that 50% of respondents had failed to reproduce their own work. There is evidence that data availability increases reproducibility, as reported in a review of Nature Genetics papers and elsewhere.
The results of this survey would suggest that funder mandates are not a key motivator for open data.
The data in this survey show that researchers are using others’ research data (49%), or would be willing to do so (80%). Yet only 60% of respondents make their data openly available “frequently” or “sometimes”. The most common ways of sharing data are still supplementary information in a journal article or peer-to-peer. Perhaps more concerning is data storage and data management. Only 20% of respondents had prepared a data management plan, and the most common ways to store active and archived data were personal hard drives, external hard drives and institutional servers.
Researchers are intelligent, responsible, motivated people. They are also time-poor, and do not necessarily want to become data or licensing experts. So they need clear information, simple policies and advice. They also understandably prioritize advancing their field, their own research and building their careers. So they need tools to make data sharing and management easier, and credit and incentives to make good research data practice and open data worthwhile.
To effect change, government, funders, institutions, libraries, publishers and researchers themselves all have a role to play. Here are areas this survey has prompted us to think more about:
More than 50 funders now mandate or encourage data sharing, compared to 28 in 2015.
The role of government
It is interesting to see the support for national mandates for open data in this survey (55% of respondents). Many countries have now made government data open, providing the best use cases to date for economic and social impact of open data. When it comes to research data, national approaches and infrastructures will continue to need similar long-term commitment, and to be balanced with fostering international collaboration, including through global discipline-specific data repositories.
The role of the funder
The results of this survey would suggest that funder mandates are not a key motivator for open data. This contradicts the findings of other studies, and is contrary to what we see as funders’ crucial role in effecting change. The growth of open access publishing was driven in part by funders issuing clear and specific mandates, explicitly making funds available and making compliance a requirement. Springer Nature tracks funder policies on data to help provide advice to authors on compliance. Encouragingly, more than 50 funders now mandate or encourage data sharing, compared to 28 in 2015. As yet, only a few funders have requirements for data management plans or data availability statements, or explicitly make funding available for data management, storage and curation.
The role of the institution
Institutions and libraries have a key role to play in supporting researchers: helping them understand and comply with funder requirements, training, establishing local research data management solutions and support where needed. Partnering with data initiatives, repositories and other useful parties, including publishers, will help reduce potential duplication of effort and ensure sustainability.
The role of the publisher
Concerted efforts by governments, funders, research institutions, publishers and researchers themselves are needed to make widespread open data a reality
Publishers work closely with researchers at many stages of the research process, particularly when they are writing up and sharing their findings. Here are five actions publishers can take:
1) Continue to advocate for good data practice across different communities.
2) Encourage good research data practice and open data through journal policies and author information: see for example Springer Nature’s standardized research data policies, Research Data Support Helpdesk and recommended repositories list.
3) Provide credit mechanisms for good data management and open data: through data publishing, registered reports, data citation and linking, and new mechanisms such as badges for open practices.
4) Offer solutions to help researchers share their own data, and discover and use data: for example our pilot Data Support Services, which help researchers deposit and curate data, in partnership with Figshare.
5) Partner with the research community to build shared solutions: for example, the global Research Data Alliance (RDA) interest group to improve research data policy standards, data linking and citation.
A number of other publishers including PLOS, Wiley and Elsevier are also taking some or all of these steps. Concerted efforts by governments, funders, research institutions, publishers and researchers themselves are needed to make widespread open data a reality, and make research data management the new normal. Collaboration and partnerships between these groups will make that happen faster, and more effectively. Springer Nature looks forward to further playing its part.
What are the best ways to visually enhance online articles?
More and more journalists are finding ways of telling stories through visualisation and chart building platforms to enhance a story with visual content like infographics and interactive content.
Justin Arenstein, director of Code for Africa — the continent’s largest network of data journalists / civic technologists, says the organisation helps newsrooms adopt cutting-edge digital tools (by funding newsroom reporting projects, embedding technologists into newsrooms, and pioneering new technologies for newsrooms). “We believe that interactive visual communication helps decipher complex economic and financial concepts for audiences … and that digital interactives that are data-driven help journalists personalise the information in ways that makes the news / reportage more compelling and relevant to audiences,” he says.
Chart building tools offers slightly different solutions to everyday problems facing newsrooms and their audiences. “Some are designed for better resources / more sophisticated markets, where newsrooms have in-house designers / data analysts to help craft the chart or interactive,” Arenstein says. “Others, like DataWrapper and Atlas and HURUmap are designed for newsrooms with limited resources and where journalists have limited skills. These easy-to-use tools are designed to run off simple spreadsheets, to help simplify the backend requirements for newsrooms.”
We spoke to journalists about some of the chart building tools they use in their newsroom to enrich their stories.
Infogr.am, a web-based data visualisation platform, is one of the easiest infographic and chart making tool that can be used by any newsroom. Journalists are able to create fast charts and infographics that are interactive for the users, as well as web responsive so they work on mobile phones. The charts can either be embedded or downloaded for publication on any site or document. It offers a wide range of high quality templates, pre-set colours, allowing users to focus on the data, while Infogr.am takes care of the aesthetics.
SABC Digital News and Hacks/Hackers Johannesburg’s Siyabona Africa uses Infogr.am to meet the changing ways audiences consume news and information.
How do you use Infogr.am? I have used this tool to create interactive infographics and interactive charts that get embedded in stories or on our live blog.
The positives: The tool works on a freemium model (so you can access it and create a set number of infographics for free); Lots of palette choices when creating charts and infographics. You can upload data in a number of formats (CSV, JSON, Excel, even streaming APIs).
The Negatives: Most of the advanced features are only available to paying members. You can save your infographics/charts as PNGs/JPEGs if you’re not a paying member.
The major disadvantage is with its freemium model which limits the functionality for some users (mostly newsrooms/organizations that can’t afford the monthly fee in Dollars and Euros). While one won’t say that they shouldn’t raise money to pay to keep the lights on, it’s hard for newsrooms to fully take advantage of the platform.
Examples of how Infogr.am can be used: Most datasets can be turned into gorgeous infographics with Infogr.am i.e. election results, job numbers, even the Mayweather/McGregor fight in numbers.
Atlas is a free data visualisation and chart building platform . Quartz, the business news service, recently launched Atlas for Africa, which aims to grow a database of Africa-related data resources for storytelling and collaboration. Users are able to create and share charts that they would have made.
Every chart published on Atlas has its own page, making it easily accessible for other users to embed it elsewhere, to use it as an image or even download the underlying data.
Adam Oxford, a freelance journalist and also working with Code for Africa, which funded Atlas in Africa, may have a bit of bias but gives good insight on using the platform.
How do you use Atlas? Honestly — I generally haven’t in the past. I’ve used Chartbuilder on which it’s based an awful lot, though. The move to Atlas came with the need to register and host data on Quartz’s site, which I never quite got around to.
The positives: I do love looking at the Atlas feed — I find looking at charts other people are creating really inspirational for developing story ideas. And the benefits it’ll bring to accessible data in Africa are really strong, as newsrooms gather and share their stats using it.
The Negatives: You may not want to publish the data behind the chart, I guess, in which case Chartbuilder would be better for you. Also, even though a chart is easy to make in Atlas it doesn’t mean it’s the right chart — too often I see journalists include a chart because they’ve been told they should, but they haven’t been careful enough in selecting the data/scale/axes to tell the story clearly. Some numbers on a graph is not a story.
I also see people using inappropriate graphs a lot — particularly when there are three variables involved.
It’s great that Atlas steps up from Chartbuilder in encouraging journalists to share their data, but it can mean that there’s a danger of misleading people if they stumble on an out of context graph (i.e. if the journalist hasn’t linked to the story in the ‘This Chart Appears In’ box.
But on closer inspection there’s a lot of detail missing. What do the percentages on the left axis represent? Do the girls receiving “no social grant” receive other income or not? There’s a lot of assumptions I might accidentally make because the story seems so strong.
Examples of how Atlas can be used: Pictures tell a thousand words, and there’s no story that couldn’t include a chart if we thought hard enough about it. What Atlas is great for is that it only makes charts that are easy to read.
There are many more chart visualisation tools that you can use in the newsroom and this list is not exhaustive. Here are some applications and online tools you can use:
Scientific research generates an immense amount of data. It is critical to not only make this data available to research community but also use it to decide on the next experimental question. Not all members of the academic publishing industry are in support of this kind of open access, which means that data remains trapped … Read more
Providing an analysis of Open Data and Open Science policies across Europe, has released a new report. Produced in collaboration with the Digital Curation Center (DCC), it follows on the heels of a previous work that listed national research data policies.
In a networked world, the best way to become a dominant player is to be an indispensable partner.
“Today, we’re entering a new era, where open platforms are going beyond just software and starting to take hold in everything from scientific research to manufacturing. In fact, as our ability to connect to ecosystems of talent, technology and information continues to increase exponentially, the solution to many tough problems is becoming more social than technical.”
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A review of the first month of Wellcome Open Research by Michael Markie, Publisher, F1000, and Robert Kiley, Head of Digital Services, Wellcome.
It’s been just over a month since we launched Wellcome Open Research, and already we are seeing researchers embrace the opportunities that the platform presents to enable them to share their work openly and without delay. The first set of articles published are a testament to the initial goals we set ourselves: making research outputs available faster while supporting reproducibility and transparency.
The story so far (you can also view as a PDF here):
At the time of writing we have published 31 papers from 232 authors who represent 62 institutions – including Wellcome research centres and institutes and major overseas programmes – covering 17 different countries. The demographic of authors spans a wide breadth of career stages ranging from Masters students all the way to Senior Investigators.
“I would strongly encourage other Wellcome grant-holders to publish on Wellcome Open Research. I think it has real potential to improve the standard, speed and fairness of scientific publishing.”
Charles Bangham, Imperial College London
There are currently 31 published articles on Wellcome Open Research. These cover a wide range of subject areas, including cell biology, genetics and genomics, infectious diseases, public health and science education. So far, the articles have attracted considerable attention with nearly 12,000 views and over 1000 downloads. These metrics are further enriched by Altmetric data which shows the level of community engagement through Twitter, news outlets and other services.
The published research also covers a range of article types from the traditional “research article” through to study protocols and data notes. In total the breakdown of publications by article type is as follows:
10 research articles
8 method articles
4 research notes (shorter articles with a few descriptive figures/tables)
3 data notes (descriptions of datasets that include details of why and how the data were created)
3 software tool articles
3 study protocols
As the platform requires that the source data underlying the results are made available the published articles make clear where these data and code can be accessed. An analysis of the data and software availability statements – a mandatory piece of metadata for all articles – reveals that there are 41 open datasets in public repositories such as FigShare and the Open Science Framework, 15 datasets available in established, field-specific repositories such as the ENA, Genbank, NCBI GEO and PRIDE, and seven cases of software source code being made permanently available in Zenodo. Making the data and software code available enables readers and users to reanalyze, replicate and reuse the data from each article.
At the time of writing there are 44 open peer review reports online which have been collectively viewed 904 times. Reviews are accompanied by the reviewers’ names and are individually citable as they all receive a DOI. Reviewers for Wellcome Open Research are also taking up the option to add their reports directly to their ORCID account to show a record of their report and enable them to get credit for their time and expertise:
Peer-review displayed on an ORCID account
The most impressive aspect of the peer review so far is the speed. The median time to the first referee report for an article is 8.5 days and the median time for two referee reports is 16 days; this is remarkably quick compared to the traditional peer review system.
Wellcome Open Research is centrally funded by Wellcome, so authors do not have to deal with any article processing charges (APCs); the costs are automatically covered allowing authors to quickly and efficiently submit their research without this burden.
We also know that most research is the result of collaboration and funded from multiple sources; just over half of the articles published on the platform include non-Wellcome funding information. Linking funding information directly to research outputs helps to improve grant-related impact tracking; these funding data are important pieces of an article’s meta-data and are deposited with CrossRef.
All in all, it’s been a hugely positive start. We hope to continue with this success next year with more Wellcome-funded researchers seeking to benefit from the platform to share their work in an open and reproducible way. There will also be some exciting new features added to the platform in 2017, so to be kept abreast about these new developments please do sign up for more information via the Wellcome Open Research homepage.