Tag: Love Data

Love Data Week – Friday – Support for Data Management

15th February 2019

Finally, Friday is all about you!

Hopefully by now you have had time to fill in our short survey – it will take you less than 5 minutes, go and do it now, I’ll wait here…

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Welcome back!

The survey you just completed will help us refine our services in Greenwich Research & Enterprise to better help you with your data management needs. We do have research data management support available in GRE already, for example:

Working with your data –  Whether it is advice about organising your data, protecting it, anonymising it or selecting what data you want to preserve, the team at GRE is happy to discuss techniques and issues with you.

Designing data management plans – GRE is able to support you in developing and writing a Data Management Plan, whether for your own records (which is always a good idea!) or specifically tailoring ones for funding applications in addition to support with the rest of your application from the Research Development Officers.

The university also has access to DMP Online, a service provided by the Digital Curation Centre, a brilliant source of advice and help about data management and preservation. They also publish downloadable guides to everything data! Using DMP Online to create your Data Management Plan will provide you with a custom list of questions that will lead you through the requirements of your specific funder, and you can share it with your co-investigators to collaborate. You can also send it over to us in GRE.

Choosing/using data repositories – GRE can guide you through the process of selecting an appropriate repository for your data, and ensuring you meet all your funder or publisher requirements.

Love Data Week – Thursday – Open Data

14th February 2019

Open data for government, citizens, researchers, and businesses can mean very different things. The people who created the Open Data Handbook describe it as “…data that can be freely used, re-used and redistributed by anyone – subject only, at most, to the requirement to attribute and share-alike.”

In 2016, the FORCE11 community released the Fair Data Principles, which have driven the open data discussion across many research communities. In the EU, this movement has developed into an implementation effort due to the GoFAIR Initiative. In the US, the Enabling FAIR Data Project is working to “develop standards that will connect researchers, publishers, and data repositories in the Earth, space, and environmental sciences to enable FAIR (findable, accessible, interoperable, and reusable) data on a large scale.”

A wide range of funders and publishers worldwide are supporting Open Data, and as such it is much more common to be required to make supporting data available online. There are numerous repositories for data available online, as listed on re3data.org. Often these repositories will support the FAIR principles but there are some things you should consider:

Findable: Make sure your dataset is able to have a persistent URL that you can share, a DOI is ideal for this as it is unique to your data and will have appropriate metadata to make it distinguishable. It also has the additional benefit of making your data trackable using tools like Altmetric.

Accessible: Make sure that your data can be found, both by people and computers. For example, when looking at repositories for data it is worth making sure that the data will be able to be found easily by others without a fixed link, for example by simply using a search engine.

Interoperable: Check that the file types you are using is sustainable (aka not tied to one specific programme unless absolutely necessary) and that the repository is going to keep and protect your data long-term. It is also essential to write accompanying documentation to your data.

Reusable: The data should be sufficiently well-described and rich that it can be linked or integrated with other data sources and have rich enough metadata to enable proper citation.

Love Data Week – Wednesday – Data & Digital Literacy

13th February 2019

Fake news or not fake news?

The world of social media, and the ever increasing volumes of information available on the internet has led to the crisis of so called ‘Fake News’ – information and data being misrepresented, or even just mis-stated to push one agenda or another. So how do you judge the legitimacy of what you are reading?

The term digital literacy has been coined to describe “the ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills.” (American Library Association)

There is a fantastic tutorial from the Open University that uses the acronym PROMPT to lead you through assessment of any sort of information, digital, data or otherwise. There is also fullfact.org which is an independent fact-checking charity based in the UK which focusses on checking statistics and data cited in news and the media.

Finally I would recommend looking at digital-literacy.org.uk which offers a whole curriculum, aimed at promoting digital literacy to children throughout their education. While this is a university, and there is a certain amount of assumed knowledge, the resources are still very useful and go into significant amounts of detail!

Data Literacy

Often thought of as a sub-division or a specialist application of digital literacy, data literacy means having full confidence to read, work with, analyze and argue with data, understand and be able to access quality data as well as combine and interrogate data and findings.

The reasoning behind the link often made is clearly shown in this page of the journalism handbook which walks you through some thinking exercises with commonly cited data types in the media.

The next steps in data literacy beyond the ability to recognise questionable data presentation and query statistics is to work with data. There are two very good free sources of data literacy training, Qlik has a very good free Data Literacy course that covers everything from Data Fundamentals to Advanced Analytics skills, and then there is the Data Carpentry website that aims to build coding and data analysis skills beyond the Qlik programme by providing training into specific data analysis techniques such as working with Geospatial data or using Python and R to analyse data.

Love Data Week – Tuesday – Everyday data

12th February 2019

One thing that we don’t focus enough on when talking about Data from our seats in an academic institution, is the everyday sort of data, the kind generated when you use social media or collected when you use almost any web service, or the kind you consume every day reading the news.

There is now a huge industry built up around collecting and sharing your data, and for the most part, information on everything you do online is collected and often sold on from sources such as social media, online retail shopping sites, and cell phone providers. For example, this article about the “Insane Amount of Data We’re Using Every Minute”, says Twitter users send 473,400 tweets every minute and Amazon makes $332,876 per minute in net sales. Facebook is collecting user data and interests from your posts and likes. Insurance companies are using your personal data to make risk assessments and determine healthcare costs, and insurance rates.

Data is also part of our daily lives in many ways. The persistent claims of “fake news” and fake data” are in the news daily and require citizens to educate themselves to determine what is true or false. Cherry-picked data are often used to support claims by all types of media outlets, without consideration of bias. Statistics and numbers about healthcare costs, election polls and voter turnout, or unemployment numbers also proliferate across our news sources. Everyone needs to be data literate, which is the subject of tomorrow’s blog!

While this all sounds concerning, data can also be an entertaining and enriching part of life. Participating in citizen science activities such as bird watching and tracking through the iBird app can assist researchers and scientists while you are enjoying a hobby. The quantified self movement has been fueled by the availability and ease of tracking with mobile devices. There have also been great successes with crowd-sourcing, the BBC has used viewers of Stargazing Live to help process huge amounts of images from space and identified new solar systems, and the British Library had the Mechanical Curator project which crowdsourced image identification by getting members of the public to add tags to images.

Protect yourself online

Would you tell a complete stranger where you went last night? Would you give a stranger your address or the keys to your house? Would you send pictures of your children to just anyone? Obviously not! but every day, people give away this information on the web, whether they intend to or not.

When a web site or social network is asking you to provide personal information, make sure you know who will have access to this information, and how it will be used. If you aren’t comfortable, don’t do it!

  • Always check privacy settings and security
  • Be aware of who can benefit from your personal information
  • Protect your identity
  • Be aware of cookies
  • Be careful what you say and show
  • Check settings and security

Before you disclose any personal information, always make sure that you are using a secure site. A secure web site will display a padlock icon in the bottom right hand corner of your web browser on in the address bar.

Check the privacy statement of the site you’re using to see what you’re signing up and agreeing to (e.g. will they protect your details; do they take ownership of the information you put up there; do they enforce their privacy statement?)

Protect your identity, and remember that things posted can spread, as a rule; if you don’t want your boss to see it, don’t post it!

I always use this example of how much information can be easily accessed by not using the privacy settings properly on social media. The video is a few years old but it still makes a great point…

Love Data Week – Monday – Help us help you!

11th February 2019

Welcome to Love your Data Week!

This week we are going to be talking about data from all perspectives starting with an investigation of the data that underpins the research that is done here at Greenwich! To this end, we are launching a very short survey to help us understand what data everyone has out there, so we can work towards better supporting you in appropriate ways!

Please take 5 minutes to fill in our survey – even if you don’t think you work with data, or don’t do it often, we would still appreciate your contributions.

So what do we mean by data?
Data was defined by RCUK (2015) as the evidence that underpins the research conclusion. While there are many other definitions, this is by far the most inclusive of the wide variety of research that is undertaken at Greenwich. This definition can include anything as ‘evidence’ from things you automatically think of when someone says data, like spreadsheets and code, all the way to transcripts, models, images, recordings, experimental observations, even collections of archive material…

If I’m honest, ‘data’ probably needs to be redefined as ‘evidence’! But until it is – help us, help you – Take 5 minutes to tell us about your evidence!

Love Data Week
Love Data Week (formerly Love Your Data Week) is a worldwide online event that was designed to raise awareness and build a community to engage on topics related to research data management, sharing, preservation, reuse, and research data services. Over the last few years Love Data Week has grown exponentially with a focus on social media. This year’s theme is ‘Data in Everyday Life’.