NIH Data Sharing with Figshare: a demonstration of getting started with data documentation and publishing

0:03Hi, everyone, and welcome to the Figshare webinar today, NIH Data Sharing With Figshare. I hope you can hear me, and I hope you can see on the screen, But if you come see, say, in the questions, or the or the chat box, and hopefully, we can iron out any any difficulties. And there's quite a few people already on the line. So I'll kick off with my small housekeeping this, and then I'll pass over to Anna for today's presentation. So as, I'm sure you can tell, you're all in listen only mode, but as mentioned, if you need to ask a question, or get some clarification, please use the Q&A box, or the chat function, and I'll be monitoring both. We'll have some time for Q&A at the end. There is a thing I can resolve in the chat. I will do so throughout. We are recording today's session, and we'll be sharing with everyone that registered in the next couple of days, or early next week. So if you have to drop off at any point, or if you'd like to share this with a ...

1:03Holly after, you will receive the recording, and then it will be available on our website as well for you to view on demand. So I think that's about all from me, so I'll pass over to Ana for today's webinar. Thank you.

1:19Thanks Laura, and thanks everyone for joining us today. I'm really excited to talk with you about NIH data sharing in FIG share, especially now that we have the new NIH data management and sharing policy in effect as of January 25, almost a whole month then. And so we'll talk today, about the different types of data, and what you can share and Figshare, and how to get started with a little demonstration.

1:49Next slide.

1:53Yes, so a little introduction to Figshare as a research repository, If it's new to you how Figshare will meet the and I miss most of the NIH's desirable characteristics data repositories, which you may have seen outlined in their policy and guidance.

2:10And update a little bit of the work that we're doing with NIH as part of the generalist repository ecosystem.

2:18Some information about types of data and what you can share in Figshare, How to include Figshare in NIH data management, and sharing plans, and budget for those data sharing costs. If you have large data, FIG share dot com is a freely available repository for both upload and download for sharing data. We do have a paid option for very large datasets that you may want to plan for.

2:43Then I'll do a little bit of a demonstration. I've often done these webinars, just a screenshot of the upload and data documentation process. So if you're looking for those slides, go back to our webinars from last fall. You can find a number of them shared, and you can see the full slide deck.

3:03And today, I'll hop over to the demonstration or how to upload and document datasets.

3:10All right.

3:12So for anyone who's new to Figshare, we're a trusted, cloud based repository for storing, sharing, and discovering research outputs. We were built. We started 11 years ago now at this point, just having celebrated our 11th birthday last month.

3:29And we've published more than formerly in research outputs from researchers around the world, at this point, hundreds of terabytes of data stored, and that work has been cited more than 100,000 times. This includes datasets, but also includes any scholarly outputs, so also code.

3:50Workflows, images, videos, multimedia files, Also presentations or posters, any things scholarly that someone wants to make sure they can share publicly and get credit for and get the citations for.

4:05We also power research repository infrastructure for more than 80 research organizations.

4:12So some of you may have available through your funder or your institution, a Figshare portal, a Figshare for institutions, we basically took our policy compliant Figshare infrastructure and made that into customisable out of the box SAS repository.

4:34So a little bit of a moment to pause and look at the history of data sharing policies since this webinar's focused on NIH data sharing.

4:45We have the 2003 NIH Data Sharing policy, which has just now gone out of effect with the 2023 1, And that one required data sharing for very large awards.

4:59We've had a few other policies in the US Federal landscape. So, if you have NSF funding, you may know, they required a data management plan since 2011.

5:13There have been a couple of directives from the White House, from the Office of Science and Technology Policy, one in twenty 13, about data sharing and public access to federally funded research, and another one just last August that directed all federal agencies, regardless of their expenditures on R&D.

5:35So all of them to create public access plans that states how their publications and datasets and research outputs will be made publicly accessible as much as possible. And the NIH has just released their new draft plan in response to that OSTP requirements earlier this week. It really builds off of the data management, and sharing policy that went into effect in January, the data component. But of course, this also impacts publications as well.

6:12So if you are an NIH funded researcher, do look for changes there, including, getting rid of the embargo, or publish papers, to make them public, to make them open access in PubMed Central.

6:27So, this is the now, current data management sharing policy. You can find a lot of information here at sharing dot NIH dot gov, I would encourage you to look at the resources NIH has put together, if you haven't done so already.

6:42They have an FAQ. They have templates for data management plans.

6:46Lists of resources. And so, you can find out more about, really all the requirements, and, of course, also, make sure to check with your specific Institute or center that funds your NIH work.

7:00Because there are variations in how each institute will be implementing the policy, what program officers will be looking for in the data management plan.

7:12But overall, the very top level of this policy, to make sure that we're on the same page.

7:18If you're, if you're not aware yet, because it only affects new awards, start in January 25. So, if you haven't haven't submitted an award recently, all NIH funded research generating that generate scientific data.

7:32So say, excluding Training or workshop grants, will require a data management insurance plan to be submitted and evaluated on an ongoing basis.

7:41But this does include extramural awards, as well as contracts, and intramural research projects if they create scientific data.

7:50And my understanding is that the intramural research community has already generated, now these plans, for all of their ongoing work.

7:59Scientific data are defining as the recorded factual material accepted in the scientific community that would be needed to validate and replicate the research findings. So it may be data that supports a publication.

8:13Or perhaps not, it could be support in support of an overzealous, or something that didn't get published a replication And if it's possible to share it, they want to encourage broad sharing of this data.

8:28And to do this, you want to, Do you want to maximize that appropriate data sharing as much as possible? And in their FAQ, they talk about some reasons that are not good reasons for not sharing the data.

8:39So some data truly must be restricted sensitive, includes human subjects data that simply cannot be de identified properly. But there are cases where you should plan to de identify it as, as much as possible, or you maybe need to share it in a more restricted fashion, and, and so forth. But reasons, like, oh, I don't think anyone would find the data useful They've said, are not a good reason. Please share. As much as possible.

9:10So yeah, here's the things that NIH is encouraging. making the Data Fair.

9:15If this is a new acronym for you, it's stands for Findable, Accessible, Interoperable, and re-usable. And it's sort of the next big frontier in open data.

9:27So making data not just open, not just posted somewhere with a link but actually documented, licensed, discoverable with persistent identifiers, documented, so it can be re-used, formatted.

9:43So it's interoperable, and so forth. So that data's not just open but truly re-usable.

9:50The NIH is encouraging researchers to share data in established, trusted repository. So that's why we're here today, who are one of those options, or researchers. And they outline, you know, maybe some of the standards, these research these repositories might want, shouldn't eat.

10:08But they're not stipulating a specific repository that must be used. But they do encourage the use of discipline, or method specific repositories, first, if they exist. This enhances the discoverability and re usability, right?

10:22Discipline specific repositories can have much more narrow metadata requirements because they only take certain types of data and can really tailor themselves to those use cases. So it does presents for reusability, but a repository like Figshare offers very broad flexibility on the other side of the spectrum and you need to use both in certain cases. So, using trusted generalists and institutional repositories.

10:52It's also encouraged, and you're also encouraged to plan for allowable costs, for data sharing in the budgets, and these lands will be reviewed by program officers so you can reach out to them with questions as well.

11:08So, broadly speaking, very simplified: we have a NIH research data ecosystem that's comprised of a few different types of data repositories, and those include those domain specific or discipline specific repositories. So Genbank Protein databank, open neuro, you may be required by H, by your institute to deposit certain types of data in one of these genomic sequences, for example.

11:41Then your own institutional repository. So your institution may have a resource, it may be powered by a Figshare, it may be on another platform, and similarly meet these flexible in general. But you need to be a member of that institution to use it.

11:57Then you have just repositories, which is where the Figshare we're talking about today would fall in. So they offer that broad flexibility and are available for anyone to use and often to share many more types of data or research outputs as well, which is true for Figshare.

12:16So, NIH has some guidance on their site, as well, about selecting a data repository, And you can see here, they give an overview, and they outline these desirable characteristics for all data repositories, as well as some additional considerations for human data.

12:34I would say that Figshare should only be used for de identified data, sensitive data, or identifiable data should not be shared on picture, and that would be in the terms of use for summer, uploading to ensure they're fine.

12:53But when you look at this list of generalist repositories, the NIH provides, they have a statement about encouraging the use of those discipline specific repository's.

13:05But noting that there is the flexibility and the need for generalist repositories. That can access data across multiple types, forums, contents, or disciplinary focuses.

13:18So here's those desirable characteristics. It's a fairly long list from NIH.

13:23In fact, it could be fairly overwhelming as a researcher to try to decide which of these repositories meets these requirements and to what extent and wishes, right, For your data or yours in a specific case. So we do have a help page that outlines how Figshare meets these requirements.

13:44Excluding the human subjects and the restricted access requirements, we meet nearly all the other requirements, but fully, including those for open access, persistent identifier, sustainability of the platform and the preservation of the datasets over time tracking provenance, providing clear use guidance through standard licensing privacy policies. We offer a little bit of a way to restrict access as well with an embargo, although it's still shouldn't be used for sensitive data.

14:21I want to make mention of a program that we're a part of FIG share so this is the NIH Generalist Repository Ecosystem Initiative or gray. We're actually just about to start year two of this program is sponsored by the NIH Office of Data Science Strategy. And it's a really interesting initiative it brings together seven different generalist repositories that serve this NIH data sharing community. Dryad Dataverse FIG share, Mandalay Data, Open Science Framework, Dibley and ....

15:02And it brings them together to enhance our support for NIH data sharing and for discovery and tracking of that data.

15:11Because not only does NIH have this policy that you must share, but they will also be looking to see that the data is shared, tracking its impact, and then looking to see how it's re-used over time.

15:24So this program, the concept of co-op petition and it says so, Competing and co-operating, merge together, but that's what all of these repositories are coming together to do. You know, we all have a lot of common characteristics and so we are enhancing those using common metadata standards.

15:46Common metrics, making sure that data you put in one repository isn't siloed there and discoverable across indices and that this is a fully interoperable ecosystem of repositories. And so, look for more product work that we're doing.

16:05That's funded by bats and and work from collaborative work from all of these repositories.

16:13All right, So, I've mentioned a number of features a Figshare at this point, but I want to highlight a few specific ones before we jump to the demo.

16:24So, here's a few at the top level.

16:27Flexibility is the first one.

16:30So, I've mentioned this. So, Figshare allows you to share any research outputs.

16:38Or files, really any scholarly output that you have created that you're the author of.

16:45And of course, you can have many co-authors in terms of file size.

16:49Make sure that our free version allows you to share files and data sets up to 20 gigabytes at a time, although you can publish 120 gigabyte dataset and then another, it's the, it's the upload, It's the limit that's on a single file or a single item at a time, but we also provide support for big datasets for Figshare plus up to many terabytes, which I'll also show you.

17:17I will offer a preview of the files in the browser. Can play videos, molecules spin around.

17:24This helps, so people can see your files without necessarily downloading.

17:29And then we also offer collections where you can group together related materials with a single digital object identifier A DOI, which is a suitable persistent link.

17:41And make sure that someone can find not just the one dataset you shared, but all of the datasets, encode, or whatnot, but are associated with a specific paper project.

17:51So here's a few examples of some published records in FIG share this to highlight that.

17:57So you can have one file in an item, as we call it, item being this big share page with a title, a description, metrics, used downloads, citations, a citation. Would an item has a citation. It includes that persistent DOI.

18:16So, you can have here, for example, 10 different movie files, or you can have a spreadsheet which can be previewed. You can flip between tabs of it Or you can have many files, including what's shown on the right here, which is a zip file or an archive where someone can preview through all the files.

18:34And very excitingly, later this year, we're going to be launching new functionality that will actually allow you to upload folders. So, at the moment, the best way to preserve file hierarchy is to upload a Zip or another type of compressed file. But, later this year, we'll offer folder structure within Fisher.

18:54I'm looking forward to that product development.

18:57And here's a few other types of scholarly output. You might share, some teaching materials or workflows demonstration, this, a poster from a scientific conference.

19:08All of these can be shared Figshare as well, and give you that persistent suitable DOI to it, to share it with colleagues.

19:17Even post tenure own research website, and whatnot to make sure you get credit for it.

19:22And here's an example of the collections. So, this is a collection, you'll see, it looks similar, it also has a title. It has description. It has metrics.

19:33It has a citation and a DOI, but it actually doesn't contain any data files itself. What it contains is these 13 items, which are dataset item types.

19:46And each of those also has their own description and their own DOI. But this is the grouping of them in a public collection.

19:57OK, a few other things a few other features of Figshare we try to meet researcher workflows where they exist. So we offer FTP upload as well as upload through the browser of course, as well as an open API which is available for upload and download files.

20:19You can use this if you want to upload many files with the same metadata on Batch upload and you can also use it to examine the contents of FIG share all of the metadata and Figshare license, CC zero and is available to the access via the API.

20:37We also offer integrations with Git Hub, Gitlab, and Bitbucket.

20:41So this is a great way to share, sought snapshots of a repository in these tools that you might be using for version control and software code development.

20:54They're great tools, but there don't really like repositories because they don't necessarily have that persistence, attracting, and so.

21:05Using these integrations where you can do is take a snapshot of the repository and deposited in FIG share and that will be at that moment in time what that repository, what that GitHub looks like, and it will be more excitable, and track more discoverable. And if you want to create a new version of it, the ... version controlled, and you can push a new version from GitHub.

21:32We offer some collaborative spaces and some options for restricted access as well. So you can add an embargo to Intuit entire item, or to the files, for a period of time.

21:44Say, for example, you're waiting for a publication to come out, SPE, published in a Journal. You can set an embargo on the dataset files to be released at the same time.

21:56Um, I have, yeah, so here's the deal, was, persistent metadata is really important, and what, it's, what helps keep this whole research repository ecosystem, I'm going and trackable.

22:12So it's really important for NIH and for everyone looking to re-use this data and make sure you get credit for it. So that DOI that I've mentioned, Figshare uses data site to assign these. That means we use data sites, standard metadata fields. These can be found that indexed across Google.

22:32Google dataset search, Data Commons, and dimensions, another another index.

22:39These DOI's are unique and persistence and version controlled as well. And also very importantly, they can be reserved ahead of time, so you don't have that chicken and egg problem about, Oh, I need to polish the dataset, but I have the paper, and how many they get the dataset DII to put in the paper. You can create a draft item and Figshare, pre reserve that DOI and you'll never worry that you didn't get the DOI into the paper. The dough I will go live when you publish the data sets.

23:11Um we have orchid integrations, orchid is a persistent identifier for authors.

23:16This is really important to make sure that you get credit for all of your work and everything that you publish on the Figshare will then show up on your ORCID profile as well.

23:25So it's a good way to track all of your research contributions, sort of across publishers at for-profit works.

23:32You can, with Figshare, link from the dataset or research output, you're sharing to other related materials, such as the related publications.

23:44And this is important for building a network of those DOI's and how they're related to each other.

23:52And similarly, linking to your funding, very important for NIH, to know which grants or grants funded this work, and be able to trace the work to them.

24:03And we have an integration for that that I will show you where you can actually link directly to grant information.

24:10This is the last feature slide. So, everything that is published, that's published, is made open access, all the public files, the CC zero of metadata.

24:20I'm feature dot com. There's really two main licenses to choose from ..., which requires attribution. These are Creative Commons licenses, and CC zero, which is, all right. All rights that are waves.

24:34Although it doesn't negate the academic custom to cite a dataset, and that might be appropriate, most appropriate for datasets, where, as you see why it might be most appropriate for, for text or other scholarly written outputs. But, that's up to you to decide.

24:52There's also a few software specific licenses to choose from if you're sharing code, and this makes the work all fair and discoverable.

25:02Oh, nope, there was one more.

25:03Tracking your impact.

25:05Why are you sharing data well, and I just requiring you to share it. But there's also a lot of benefits to you. Data, papers that have their data, openly shared in a repository, have been shown to be cited more frequently. And now you can also get citations of the dataset itself. And so, here's a few things we offer for tracking that impact: have a public author profile on Figshare that will show all of your work and your cumulative metrics as well as those item level views, downloads, citation metrics.

25:41Those citations are importantly pulled from the full text of the literature. So when you're citing dataset duis papers, you may find that you put them in many different places. They may go in a data availability statement or a resources section or you may cite them in the methods section.

25:59Sometimes they're in the references section and sometimes they're not. So, by looking for those dataset DOI's across the full text of the scholarly literature, it gives us a better chance of making sure that we fully capture all of those citations.

26:14And then these can be found across bitshares using our facet search features, as well as in many other indexes.

26:23Didn't include just a couple of screenshots of these here, just as author, author profiles.

26:29You can see how you can create one and link your ORCID and you can configure your ORCID. It really is through authenticating through orchids. This is a great way to make sure there are no typos in your ORCID ID.

26:42And you can choose to send your data from Figshare to ORCID or even vice versa as well if you would like to have drafts of things from your org and profile picture.

26:54And you can see that public information there.

26:58Then, here's the example of the metrics. So on the item level, this can be hard to see in the item page, but blown up. This is what those you download and citation counts look like 87 as a lot of citations. This is a software item that was cited quite a lot.

27:16And then we have altmetrics and this altmetrics badge. Matrixx is a sister company of ours at digital science.

27:24And this shows the attention to the work sort of outside of that citation ecosystem.

27:32So, now, if you think Figshare is a good fit for some of your work, how would you include it in an NIH data management and sharing plan?

27:41So in this plan, you have to think about what data will be generated and shared, and where, when and how it will be shared. So decide which types of data from your project will be a good fit for Figshare.

27:56And you can choose to use it together with discipline specific or other generalist repository's if needed, as well.

28:04You might want to group everything together in a collection, and plan ahead for these data management practices.

28:13There is a There is a help page here as well. So, again, a place of reference for later you may not be writing a DMP or a DM SP Today, but you can reference this help page later. And here's a few examples that are found on it.

28:30That are examples or prompts that I'd taken from the questions NIH would want you to address.

28:38So you can save it.

28:39The data will be shared and Figshare a little bit of information about that process, Forry.

28:45Importantly, state what types of files will be shared, and what Figshare does it gives you the flexibility to share any format, so you can here, choose those community standards that you want to adhere to. Or choose files heights that make the data and boost re-usable, open source format, for example.

29:07Just, you'll want to talk about how the data will be described. How will it be documented, formatted, again, addressing community standards? This is where you have all the flexibility.

29:18You can include a readme file, a data dictionary, and, and simply upload that file to your, to your datasets, and, and make sure that someone knows how to re-use the data that's there.

29:33You may want to talk about how the data set will be license.

29:37So, whether you will use that CC zero, or CC by license in Figshare, how it will be discovered and preserved.

29:47And here's a little snapshot of our Figshare plus repository. So this is really built on that Figshare for institutions.

29:56Custom Infrastructure.

29:58So we took our own custom repository infrastructure, and built ourselves a repository for sharing big datasets. And this really came from researchers increasingly coming to us, and saying, I need more than 20 gigabytes anymore than 50 gigabytes. I need more than 300 gigabytes of storage for this dataset, and we said, that's awesome. We'd love to help you, but storing data redundant really in the cloud.

30:24And allowing for free download if you know anything about egress fees, becomes a real cost for us over time. And NIH has made clear that they want to make sure that the research repository ecosystem is sustainable. So we've designed Figshare plus to allow us to have a one-time data publishing charge for these deposits. So this is tiered based on the amount of storage that you need for a specific dataset. So, it's really designed to be a dataset, or a collection of datasets, and encode, and other outputs that all go together that all support a single paper, or a single project that's being released. You have 12 months to upload it, but we encourage you to kind of upload it all at once.

31:13So this is just, sort of the, the maximum storage that you would need for that, and it also includes some support and data review when it's submitted, because we want to make sure that if you're sharing this dataset, and you're paying to share it, that is well described. So we do have our data review team. Check specifically the description of the metadata. Really, to make sure that the metadata is complete and high quality and makes that data as discoverable and re-usable as possible.

31:49Um, there's a few other attributes of big sharpless, in addition to just the total storage.

31:55You can also upload much larger individual files, actually up to five terabytes if you were purchasing five terabytes total. And we allow more total files per datasets, which is also flexible, if needed. We also offer more creative, very creative commons license options. So if you need to put a non commercial restriction or share like restriction on it, we offer those. But this is intended to be another way to meet those funder or publisher requirements.

32:28And with the transparent pricing, allow you to plan ahead, for including that in grant budgets, when you know you may have large data sets to share, and then helping you through the data deposit and documentation process.

32:44So, here's just an example of something and Figshare plus students. This one's quite large, nearly five terabytes total, although across 48 different files.

32:54And here's another example of a collection on Figshare plus. So these are, you can have up to 10 items in a deposit and Figshare plus.

33:05And so, in this case, it's seven different datasets that represent different portions of the projects, supporting the paper, and they're all grouped together in this collection, non-fiction, Plus, which is also a feature that we have there.

33:21OK, so I think we're going to jump into the demo now, but I wanted to point to a couple of resources for you. one is the Guide to Sharing NIH funded research on Figshare.

33:32That's on our help page also the help page for including Figshare in a DMP and the Guide to Sharing Data on Figshare Plus, which has a lot in common with NIH Guide.

33:43that will walk you through that process a little bit more. And here's where you'll go to get started.

33:49So, perfect, share dot com, if you don't have an account yet, Free and easy.

33:53Just sign up with an e-mail address of your choice on this registration page, and then you can get started with the process. I'll show you in a moment of uploading, documenting, and really self publishing.

34:08You're a research on a Figshare, you want to publish on Figshare plus, It's a little bit different. We'll get started by submitted in order request. Telling us a little bit about your dataset. Large it is, what type of work it is, Who is funded by just to make sure that we can take a quick review of it and make sure it's a good fit for the repository, and then we'll set up an invoice for the payment and set you up with a user account on Figshare Plus and a project to which the storage is allocated that you'll use. Then it will be the same process. You upload your files, you document the save them. But when you submit a Figshare of plus, they come to our review team for a quick review and enhancements That needs to be made to the metadata versus a Figshare.com. click publish they just go live right away.

35:00So, in that sense, the ...

35:02Live when you publish it, and so do you plan ahead a little bit for that support and review time Figshare plus and then I've also linked to our Figshare API. If you're inclined towards automating your data sharing processes you can find all of our documents their docs that Figshare?

35:22So that's it for me.

35:23They're going to change out of this.

35:28OK so FIG share dot com So this is one when you login and when you've logged into your account and figure it out I can show you know Figshare at coffee scroll through, so you'll find first a little bit of information and then you'll find the repository here. So here's all the public content that's on picture dot com, you can also browse it.

35:57Here by category, you can do it via searching facets.

36:03And this is really looking at millions of records that have been shared In FIG share dot com, but you could say I only want to see datasets. And importantly, everything that's in those Figshare for institutions, portals or Figshare plus, also shows up on figshare.com. So that's another way that it's discoverable and searchable, but you can restrict the source.

36:24If you'd like to just the Figshare.com items.

36:29But when you've logged into your account, then you instead see this when you login, which is your My data page. And you'll see there's a few different tabs here.

36:40So my data, which is all of your items, you'll have projects which are collaborative projects that you can share with other colleagues, to look at work you're doing.

36:53And you can have collections, which are those public collections, And you can publish a collection once all of the items that you've put in it are also accomplished.

37:04So, In your My Data. There's a couple of ways to get started with Creating a new Item.

37:09You can go and upload at the top.

37:13And that will take you here and you can drag and drop a file and that will take you right to our Create a new item page once you dragged a file or browse for a file.

37:26I'm going to not say that for one moment, but you can also go to Create new item here. that'll take you to the same.

37:34Type of form to create a new item. But you'll see I haven't added any files yet.

37:39So for that, I can browse locally.

37:45Or I can drag and drop here, if I'm using the FTP, It will deposit the files into my data as a draft item, and then I can work on completing all of these metadata fields.

37:58Um, I wanted to show you one thing about the metadata fields. Here, before we dive into what it's going to look like, sorry, this is sorry, this is Figshare Box, so this is how you would get started with ... Plus is this order form here.

38:14And then this is the FIG share plus repository so You'll see. It's got all the look and feel of all of the Figshare repositories and.

38:25I've got some cumulative metrics here which are starting to look.

38:28Pretty good for a year, for watching this repository. So here in the Figshare plus my data.

38:36Because Figshare Plus is built on the, I'm sure, for institutions.

38:43Um, Framework.

38:48All right.

38:51It's not there.

38:53You can do, you can have these custom metadata fields. And what I'm going to show you is our new edit item page.

39:01which is now, not available to me. OK?

39:04Well, in March, we're launching a new Edit item page, and this Edit item page will look a little bit different. You'll have all the same functionality. I think, actually, the user interface will just be easier to follow. I was showing you the look and feel of it today, but that doesn't look like it's built at the moment.

39:21So, it's there, and it will be launching in March, and we'll do a lot of webinars and trainings, and guys about it, But it will allow us to offer a lot more functionality, to have metadata customized by item type, and to encourage putting that high quality metadata in. So, for example: when you list of related material, not only will you just put the URL to it, but you can also say, Oh, this visit sites this, or this is cited by that, or the supports this, And clarify that relation type between items. So, that will actually be really great to have. So, But for today, we're going to work with the current look and feel of our item page.

40:05And so let's drag some files in here. So, I said, You can have more than one. So let's do a few.

40:12So, you can have an Excel file, we can have to now see that it's progressing with that blue bar, goes to green.

40:23Let's have a larger, It's a zip file, and so now you're seeing it's uploading a little bit more slowly.

40:36Hmm, I'll upload text file as well, All right.

40:43Second. Oh, we've got a progress bar, OK. So while we're working on that, let's look at the metadata fields here.

40:51So, I'll give you a few recommendations for completing, so, for the title, You really want to use a descriptive title. In fact, our tips is this right here. So if you're ever forget, what you want is something that makes this work discoverable, so best not to use the file name, or call dataset one or dataset to, or figure one, figure two. You want this to speak to the contents of the work, to the methodology.

41:23And one, you can also use the publication name in the title, if it's helpful.

41:27So some people will say, dataset supporting Figure one of paper XYZ. And that's a, that's a fine practice.

41:36You just want to It's best to distinguish the title of the data from the title of the paper, because they are different scholarly outputs. They have different DOI's. So it's best not to have the exact same title if it's possible to avoid that.

41:52So, maybe say we'll say this is a dataset of visual expertise, Test Measurements.

42:09Supporting mandich, developed expertise tests were just the paper title, right? So, that's just one example of something you could do there.

42:25Office.

42:26So it will automatically list the account you're logged in as the author first.

42:32And so you can add additional offers.

42:37And.

42:41To them we have a lot of different marks here And it'll show you can have their e-mail address or their orchid that's associated with the account, which can be helpful if people have multiple, or you're looking to disambiguate across a common name.

42:55You can also add an author that's not there. Oops, I've already done that one. Sorry. Let's try this.

43:05I'd like to add my cats.

43:08Some new kittens, so there's more cast.

43:12So if you're an author doesn't have a Figshare accounts, it's not a problem, you can still add that. And you would just add their author details Definitely the first and last name. And it's also good to add an e-mail address or their orchid ID if you can. This orchid ID does go into the author level metadata. And it helps everyone get credit for their work.

43:34So, if those exist, my cap isn't working, but it's a good idea To add this.

43:39Then, you can also change the order of the author, so you can actually be like, oh, Marx first author, and senior author, just drag and drop.

43:48And if you say F 10 doesn't do anything, just deletes, OK. Categories.

43:54So to say these, the green Circles denote required fields. So you'll see most often pictured here are required fields, but there's some that are optional. And if you're working on the FFIEC portal, you may have other optional fields as well to em, er, inscription. The Categories field gives a sense of what the general topic for this material is. What's the subject area?

44:22And you can search this.

44:28So it's a vision science, and you can pick one, or you can pick seven.

44:37And these are using the fields of research codes from Australia, New Zealand.

44:45So, this is a controlled vocabulary that we're pulling from, which does improve the mapping wissam indexes.

44:55You can select the item type. So, these are the item types that we offer on Figshare.com.

45:01You'll see here the kind of range of outputs that you can share. So, this, I would probably call a dataset, but you could have media, your determination of what's media. And what's a dataset, if you say MRI images, is that an ..., or is that a dataset that's up to you and your research community? I would say that probably qualifies as a dataset in that case, if it's being used as the primary, raw data that's being analyzed. But you may have other media files that are a demonstration of the work, or the workflow, or products, that you want to categorize. Morris Media.

45:38We've got the presentations. We've got Software, we have some tool tips here that explain, so, you can say, here, Code. So, Software code, we're using them in a little interchangeably here, it doesn't necessarily have to be executable software, but anything that you've written works that. Online Resources is a good kind of option.

46:01four, sharing, know, some some other component of the work that someone might find very useful. Or that helps clarify how the work was done, But it may not necessarily be software code.

46:16So, something like like a workflow or I've used it for Surveyed Template, for example, or test materials, does, can be assigned that option.

46:31And then you see presentations and posters as well, if those are something that you have to share.

46:37I should select one dataset, keywords. So keywords are up to you. I like to say a minimum of five keywords is useful.

46:48So you will notice that's because auto populates, and this is auto populating based on the keywords that other people have already added.

47:01And this will, you can, that's roll, scroll through fine. If you don't like that one, you just add your own, you can add your own.

47:15And so, these can be one or more words.

47:21This is, you'll notice what used to be my previous field of study that I went to draw from.

47:28As many as you would like there, the more you add, the more discoverable, the Description section, this is where you can put all kinds of content.

47:38You want to make sure this has a description of the datasets and the related materials at a minimum.

47:45Usually, at least, you know, a few lines, paragraph could be 10 paragraphs if you would like. You can put, you know, the layout of the data, the file naming schema. The files that are included linking to the publication.

48:01Linking, you know, to a preferred me now offer.

48:06We now offer links and hyperlinks and formatting, and bullet points and all of that here, so you can fill that in, and so you can get dataset supporting of this paper, files are earned.

48:22According to this, see here for more information, I like to say if you are creating a collection where you have multiple datasets. You're sharing it's useful to note here, so that someone knows there's other related materials in the repository.

48:39And so, you can really do quite a lot with this new text editor here. I'm gonna get into the weeds on formatting today, but offers you all those choices.

48:49All right.

48:50For funding, this is not a required field, ... dot com. However, I would strongly urge you if you're sharing NIH funded data, to please list your funding sources here. This really helps us track ... funded data and I'll tell you that as part of great, they are looking to see what NIH funded work is, Sheridan picture and want us to report on it.

49:15So for sharing funding here, you can add it as free text.

49:22Or you can also add by searching.

49:29Or the grant ID. So, let's see what I'm looking for here.

49:35So this R 21 beta is is the National Eye Institute Award.

49:41So, the way you want to enter these is either by the grant title or by the award information. So, this would start with the Activity code, so R oh 1 R 21 to 32, the two letter institutes code, and then the six digit serial number, or the grants. And you can find out more about that award by clicking arrow and you can say, Oh, yeah, OK, that's the right one. That's the, that's the award I was thinking of.

50:14I'm going to add that.

50:15And then, when it's published, that will turn into a hyperlink that takes you out to this information in the data dimensions database, So this is an integration with our sister company. Dimensions.

50:28If you don't have an award number or not at age funded, you can also put free text here.

50:33So you can just say, Carnegie Mellon, faculty, award, or something like that, right, and that'll just show up as free text, that's not hyperlinked to an NIH grant. But if you put the NIH grant, then that information about the funder and about the grant ID is all included in the data site metadata and really abstract work. And you can add as many of those as you would like.

50:57References are another area, so, um, references is gonna look a little different soon.

51:03But here's where you can put links. So, here I'll put a link to the related paper.

51:09So, I've just copied the paper DOI and I've added here to add more. At the moment, you would hit Shift and Return. And it will give you more references, You can add.

51:21But any URL here. And this in the future will look like adding the DOR URL and then a drop-down to state the relationship type.

51:32Lastly, in the required fields, you have those license options. So CC by CC zero that I mentioned and then the software license options, and there'll be a few more of those are on Figshare plus if you need them.

51:47So I think at this point, it's, I have everything that I would need to publish. So I could check publish, and it will let me publish that.

51:57I'm not going to do that today because we're not going to publish this and make the DOI live for this random assortment of files that are uploaded.

52:04But at that point, it just will be live within a few minutes and you'll be able to find it on FIG share dot com. And the DOI will be live as well.

52:14I mentioned you can reserve the DOI.

52:18You can do that, and it will generate this geoeye link.

52:22So all you need to do to make this into that publishable format is add the HTTPS DOI dot org forward slash before this 10 dot 6. And that will be what the DOI link will be when the dataset is published and live.

52:40So feel free to do this if your draft records put those data set DOI's into your manuscripts at the time you submit them and then you will make sure that they never get missed.

52:53There's a couple of other options here. one is to generate a private link.

52:59Here's the tips about the private link if you forget.

53:02But a private link is not designed to be shared publicly. So please don't put the public link in your paper instead of the DOI the door as the one we're going to look for citations of, and we won't be looking for the private link to capture citations of this dataset.

53:21The private link also blinds the authors, so it removes the authors from the item. You can use the private link when this item is a draft, or when it's published either way.

53:32But it works well as a draft, because then you can share this draft dataset with colleagues or with peer reviewers or journal editors, or something like that, which is really the main intended use case for this. So do feel free to generate the private link.

53:49Sharing the URL at the top of the page will not provide access to a colleague. They would need to be logged into your account, so to give them access, it's best to use this, or to use a project.

54:03The last option here is to apply an embargo, and so you'll see a few options here for how to apply an embargo. You can select a specific period of time, or you can select a specific date.

54:17You may not know exactly when, your paper is going to come out and when you want to end this embargo, and that's totally fine. You can set the embargo to just, six months, and then you can, go back into your dataset. once it's published. All of the datasets are still editable at any time, and remove that embargo.

54:37And you can choose whether you want the embargo to be on the files only, meaning, that, the, metadata and that whole page will be available and, publicly indexed, but the files won't be accessible.

54:49This has the benefit of making that metadata discoverable and also making the DOI live. So if a copy editor, and publisher is looking to see that, that dataset DOI works, this will allow them to check that while still keeping with files private, or you can put the embargo on the entire contents.

55:09You can also put a reason here. It's not required, but it's helpful. You know, you can say, I've never sharing this, because hits data that I want you to request access from me, or you can say it'll be published when the associated paper comes out.

55:27Um, I think that covers everything I wanted to talk about here.

55:35So, then.

55:40See, I'll save my changes demonstration of that function.

55:44And, so, you'll see that in my data.

55:46There's a status, here, I have these draft items of different item types, different sizes and dates, and the status icon will show that this gray circle, which means that it's a private item, which means that all the required metadata fields have then build outs, but it hasn't been published yet, if I had started it, but not filled out the fields.

56:12Yeah, it would simply be a draft, and the dark green circles are published items, and you also have embargoed, or in the case of Figshare plus you might see under review if it's with our review team, but not published yet.

56:27If you want to make edits items afterwards, you can add to a published items, to do click on the published item. It'll take you to the live page. So, here, for example, is a fact sheet that we made for the great repository ecosystem. You can see the preview of it here.

56:46And, some, metadata for it, fill that out. And you can download it.

56:53And, importantly, you can cite it so, you can choose your citation format from a very long list of options. You can copy the citation or the DOI.

57:03And this is going to be critical, when you're looking at a public dataset.

57:09This DOI's is key. And you can see here a, you know, there's a hyperlink in the description section And reference out to a URL.

57:19license appears there, keywords, categories and metrics on this item.

57:28You'll also notice that there's a dot V one in the DOA.

57:32The base DOI without any version will always resolve to the newest DOA.

57:38But you it will be versioned if you make certain changes. So if I wanted to edit this, instead of seeing the public view, I would go to this little gray pencil icon, and it will take me back into the Edit item page. I can change the files. I can change any of the metadata. And I would just note that some changes will add a new version number to the DOI and you'll see those versions as drop-down, so someone can access previous versions, as well as the most recent.

58:08And, so, that one, those changes that will trigger a new version include changing the files, changing the title, or author's or license.

58:19But if you want to simply change the description, you want to add that the associated peer reviewed paper came out now, and you want to put a link to it, And those changes will not trigger a new version.

58:32All right.

58:33I am going to stop there, because we are really out of time for today. But thank you so much for coming.

58:39And if you have questions, I'm happy to stay on and answer those from anyone and happy data sharing.

58:48Thanks so much for the presentation. We do have a few questions. So the first one for a PubMed NIH Reese, for PubMed NIH Research, where metadata wise would you put the PubMed ID?

59:02Hmm, hmm, hmm, it, so is this linking to linking to a related resource in PubMed, I assume? In which case, you would put the PubMed ID in that references section.

59:17And this is where our new references update, which is coming later this year on that Edit item page, will be really helpful, because you will be able to add, not just doe eyes and URLs, but add multiple persistent identifier, including PubMed, IDs.

59:34So, right now, you would have to share a URL in the references fields, but in the future, you could add that PM ID in that format there, and then say, this is a citing material or supporting material there. Right now, the best way would probably be to put that into the description section, or include a URL, so, PubMed.

59:58Great, Thank you, and probably related. a couple of people asked if you could just repeat when when the item page, Misstated form will be updated. I think it was March wozny, he said. yes. My understanding is marked as our product team for her more for an update on that.

1:00:14And I don't have an exact date right now, but I think the end of March is what I would look for.

1:00:23We will have, um, new news is going out, social media posts, and so forth, so that no one's caught off guard when they go. The next morning and the page looks different. I know if people have guides that they've created, I'm using Figshare because I do. Myself will want to make changes to those so we will give you some warning shortly.

1:00:46Last question we had is, which maybe I don't know, do you have a rough idea of the percentage of data stored in FIG share under CC zero?

1:00:56Ah, that's a great question. Is that an advanced? Can I searched by license?

1:01:02They say.

1:01:05

1:01:08Yeah, sure, I'll answer your question.

1:01:10So FIG share dot com datasets, CC zero license Telling me about 9000.

1:01:19If you restrict to FIG share dot com versus the CC BMI being 109 and this would be just the dataset item type.

1:01:27We did all item types Figshare dot com looking at 12,000 versus the 300 thousands.

1:01:39I think that should be pretty accurate.

1:01:41Great, thanks. And last one just come in now. Is that any use case for a researcher to choose Figshare plus the smaller day sets because of some of the other additional features?

1:01:52Yeah, that's, that's a great question. Is something we're not doing at the moment simply because we're trying to save those support resources for researchers with large files.

1:02:06But this is something we're hoping to offer in the future because we are getting requests for it either to have additional license options or maybe where our interests was most is in offering those metadata checks and deposit support or files for datasets of any size and offering sort of that I checked.

1:02:29She curation option for FIG share dot com or Figshare a plus for profiles of any size. So now I have a moment currently only datasets that are over 20 gigabytes.

1:02:40But stay tuned. We may. We may add that.

1:02:47Thank you. That's all the questions. Oh, one, which is Kevin. Is it possible to Ethan, past examination papers repository on Figshare?

1:02:56I seem to stay only if they've been shared by the by the relevant institutional teach in the room, Right. Right. Right. You're only published yet.

1:03:06Wonderful. Wow, thank you so much for the presentation. Thank you, everyone, for the questions of the joining. We'll get the recording out in the next couple of days, and forward seeing you on another webinar soon.

1:03:19Thank you.

1:03:20Thanks, everyone.

1:03:21 Bye

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