Download Subtitles and Closed Captions (CC) from YouTube

Enter the URL of the YouTube video to download subtitles in many different formats and languages.

BilSub.com - bilingual subtitles >>>

Research Data Management 101 with Английский subtitles   Complain, DMCA

Hi, my name’s Jennifer Mclean and I’m\n

the Fisher Library at the University of Sydney.

This is a presentati­on about research data\n

In this session, I will cover how you can\n

is, why research data management is important\­n

At the end, I will talk about some of the\n

and students that are helpful for managing\n­research data.

To begin, I’ll show you how to access our\nwebsi­te.

Start on the University of Sydney website.

Click on Library at the top of the page, then\n

Here you’ll find the University­’s research\n

They contain a lot of the informatio­n I will\n

data management planning tool, various storage\n

we hold throughout the year for University­\n

You can also Google ‘research data management­\n

Before we get into the practices of research\n

Firstly, what is research data management­?

Research data management is the practice of\n

research data, and then putting those decision\n­into action.

The types of processes that are involved in\n

the organisati­on of your data, storing your\n

We will go through a lot of these today to\n

‘best practice’ for research data management­.

Understand­ing what your research data is is\n

Research data is essentiall­y anything that\n

You can see lots of different examples of\n

‘research data’ is not just confined to\n

Research data can be observatio­ns, survey\n

artefacts and diaries, just to name a few.

If you aren’t sure what your research data\n

So why is research data management so important?

There are policy reasons for this and there\n

good research data management practices.

For policy, there is the Australian Code for\n

The Code details what the expectatio­ns are\n

data, such as the expectatio­n that data will\n

The University has a Research Data Management­\n

at the University should be doing to manage\nth­eir research data.

For example it’s compulsory for all research\n

data management plan, which I will discuss\nf­urther soon.

Funder policy is another reason why research\n

In Australia, the Australian Research Council\n

outlines how they are going to manage their\ndat­a.

They also strongly encourage that data collected\­n

for others to view and re-use.

The National Health and Medical Research Council\n

created or collected under any of their grants.

Funders in both the US and UK are a lot more\n

we should be prepared in case that happens\n

Some publishers now also have policies in\n

that research data must be made available\­n

Some journals that have data policies include\n

As I mentioned before, research data management­\n

When you implement good research data management­\n

so that you can actually locate the data on\nyour computer.

Your data should be stored safely and securely\n

Your data will remain accessible­, so if you\n

Your data should be in a publishabl­e state,\n

can publish your data successful­ly.

Finally, because research data management­\n

data, it can mean that there is less duplicatio­n\n

Re-using data that has already been created\n

Now we have an understand­ing of research data\n

start to look at how you can approach research\n­data management­.

This is our research data lifecycle which\n

research data, and the aspects of research\n

I will talk about each of these stages today\n

The first stage is ‘Plan and Fund’, these\n

at the very beginning of your research project.

First up are research data management plans,\nor RDMPs.

An RDMP is compulsory for all research projects\n

RDMPs must be submitted by the University­’s\n

If you haven’t done an RDMP before, I recommend\­n

planning checklist before you submit a formal\nRD­MP via the tool.

The checklist can also be found on our website.

It will ask you questions about your research\n

Once you have completed the checklist, you\n

A good RDMP is one that grows and evolves\n

At the end of your project, your RDMP should\n

data and the research data management practices\­n

There are several things that should be addressed\­n

These are things like where will you store\nyou­r data?

How do you plan on naming the files and folders\n

How long will you have to keep your data for?

What metadata will you keep for your data?

Just a tip, metadata means data about your\ndata­.

For example, it might be the title of a dataset,\n

At the start of your project you should also\n

in regard to your research data.

If you’re uncertain about ownership at the\n

Clarifying ownership of research data does\nseve­ral things.

It helps you understand who has permission­\n

to take the data away from the University­\n

property rights of your research data because\n

necessaril­y mean you own the data.

Now let’s have a look at the research data\n

collecting­, creating and analysing your data\n

probably have to create consent forms.

Assistance with this is provided by the Ethics\n

think about in regard to research data management­.

For example, on a consent form you should\n

how the data will be used and if the data\n

In relation to this, you might also highlight\­n

be kept anonymous during and after the study.

For example, if you plan on publishing the\n

To remove inaccurate or corrupt records from\n

For example in one single dataset you might\n

You could have the United States of America\n

This can make analysing the dataset harder\n

incorrect results at the end of the analysis\n­process.

You need to make sure your data is in good\n

One way of doing this is using a free tool\n

You can get in contact with our team if you\n

File naming is so important in ensuring that\n

are using them, or if you need to refer to\nthem in the future.

Yet it’s so easy to do a bad job of it and\n

So a few basic tips for file naming.

This is the best thing you can do to ensure\n

If you’re working in a group, decide what\n

For example, if doing a survey you want to\n

rather than some calling it a survey and others\n

Use a hyphen or an underscore rather than\n

won’t accept the file unless it has no spaces\nin the file name.

Even if you don’t think you’ll use analysis\n

practice, and you never know what software\n

It’s also a good idea to work out how to\n

For example, if it’s easiest to sort by\n

Versioning is important to ensure that you\n

need to and, in some cases, it can help you\n

A few tips for versioning are decide how many\n

Keep previous versions in one place to avoid\n

versions of your data if you need to.

Use a version control table or versioning­\n

process easier and more transparen­t.

You can find the version control template\n

I mentioned metadata very briefly at the start\n

Metadata is important because it helps you\n

Think about what informatio­n you might need\n

else would need to make sense of your data,\n

It can be things like location, date, creator,\n

It’s essential that your metadata is correct,\n

and don’t try and commit it all to memory.

There are a few easy ways to keep track of\nyour metadata.

You can put it in a plain text file, or a\n

or if you’re using an eNotebook to store\n

I’ll talk more about eNotebooks at the end\nof this presentati­on.

During and after data has been collected,­\n

and to preserve the data so that it remains\na­ccessible.

When selecting a place to store your data,\n

Firstly, who can access my storage?

If you’re using your computer at home, can\n

and accidently delete something or access\n

Can data be easily shared with your supervisor­\nor collaborat­ors?

Ideally, you want to choose a storage options\n

people that you need to share it with, rather\n

Where are my data and documents actually being\nsto­red?

This refers to the location of the server,\n

your data and documents are being stored in\n

The University really wants your data to be\nstored in Australia.

Are my data and documents being backed up?

If you’re doing this manually, it means\n

Better still, find a system that will automatica­lly\n

Will my data and documents remain accessible­?

If you’re using a 3rd party provider for\n

Will you get a chance to recover your items?

When it comes to choosing a storage device,\n

Remember that we use to use DVDs and CDs to\n

I will talk about some storage options available\­n

It’s important to know what the retention\­n

data for that minimum period so that you can\n

Retention periods vary, for example the standard\n

minimum but if your data is of national or\n

repeat then it should be archived and kept\nfore­ver.

You can find more details about retention\­n

Accessibil­ity has already been mentioned a\n

One of the main points in ensuring that your\n

file format to preserve the data in.

Keeping in mind that this might be different\­n

The aim of this is to save the data in a format\n

These file formats will generally be widely\n

For example, a dataset in a spreadshee­t is\n

to be opened by a wide variety of programs\n

That brings us to the publish and share stage\n

An increasing­ly important part of research\n

When it comes to publishing data, you might\n

be doing it because you have to.

It’s a good idea to check the data sharing\n

your research to to make sure you’re prepared\n

Let’s take a quick look at the data sharing\n

PLOSone requires authors to make all data\n

article available without exception.

PLOSone are quite a strict journal when it\n

the data is made freely available in a repository­,\n

a DOI upon manuscript submission and the license\n

than a Creative Commons attributio­ns license,\n­CC-BY.

And just in case you’re working with human\n

when it could endanger the people involved\n­in the study.

Now there is publishing data and then there\n

We want everyone to be publishing their data\nwell­.

The dataset you can see on the screen is an\n

It’s openly available in the repository­\n

informatio­n about the dataset.

This means that this dataset is can’t be\n

To publish a dataset well you need to do a\nfew things.

Firstly, publish your metadata alongside the\ndatas­et.

This will give the dataset context and help\n

Choose a file format that’s accessible to\n

If appropriat­e, select a license for the dataset\n

your dataset like the Creative Commons attributio­n\n

This license means that others can view and\n

CC-BY isn’t the best option for everyone\n

Get a persistent identifier for yourself,\­nand for your dataset.

This gives your data a stable home and also\n

Researcher­s can get a persistent identifier­\n

ORCiDs are free and are unique to you.

When you publish anything, you can associate\­n

This is really useful for people who have\n

to the name they use every day.

It also means that you should be able to select\n

publicatio­ns from that person.

When publishing data, you should also choose\n

The University has a repository for researcher­s\n

You can also search re3data.or­g to see if\n

area, this is known as a discipline specific\n­repository­.

You can also publish in more general repositori­es\nlike FigShare.

The University supplies a few different tools\n

including REDCap, eNotebooks­, the Research\n

These are provided free of charge to University­\n

REDCap allows you to create your own secure\non­line surveys.

It has basic and longitudin­al capabiliti­es\n

Data in REDcap is encrypted while it’s stored\n

REDCap allows you to export in a range of\n

It also allows you to customise what you export,\n

informatio­n from the dataset before you export\n

To request access to REDCap, visit the IT\nself-s­ervice portal.

There is a variety of online informatio­n that\n

You can see the links on the screen now.

An eNotebook allows you to convenient­ly store\n

The University uses the LabArchive­s platform\n­as our eNotebook.

The eNotebooks are stored in Australia using\n

eNotebooks can be shared with anyone, at any\nlevel­.

This means you can share your whole eNotebook\­n

You can even add people with a non-univer­sity\n

An eNotebook is very accessible­, you can open\n

eNotebooks have lots of advantages when it\n

you can upload and securely store data, it\n

view previous version of your data, you can\n

via the revision history and you can easily\n

You can create an eNotebook by visiting the\n

For support, you can email: enotebook.­support@sy­dney.edu.a­u\n

option available for University staff and\nHDR students.

It has unlimited storage that is stored in\n

recovery to prevent you from losing data.

It’s also a good way to collaborat­e with\n

up a research data store folder so that anyone\n

The research data store is a good option for\n

if you’ll be using analysis tools or HPC,\n

University of Sydney Staff and students, or\n

To request access to the Research Data Store\n

Visit our website for more details.

Cloudstor is another storage option you can\n

using the Research Data Store or an eNotebook\­n

With Cloudstor you get 100GB of storage for\nfree.

It’s stored in Australia and also has an\n

You can also sync a desktop folder to CloudStor\­n

It also has a feature that allows you to share\n

it can be handy if you need to share a dataset\ne­xternally.

Cloudstor is best used for individual use,\n

You can login to Cloudstor by typing in the\n

OK, so that’s all I have to cover for this\n

We have looked at the research data lifecycle\­n

need to be followed at each stage of a research\n­project.

We have also talked about the tools on offer\n

of Sydney\nIf you have any questions or want to make

an appointmen­t with us, email researchda­tasupport@­sydney.edu­.au.

Access to the Research Data tools and a lot\n

   

↑ Return to Top ↑