 Thank you. Welcome everyone and thank you for joining us for today's webinar. My name is Marisa Kings Garwin and I'm a collection digitization librarian with Harvard University Library. And I'm also a member of the DLF project manager steering committee. So today I'm going to be hearing from Molly Bragg and Louise Smith about how they use the tools Jira and air table to manage different aspects of their digital projects workflows. So just a little bit of housekeeping before we get started. If you have any questions during the presentations please put them in the chat and I'll bring them up at the end of both of the presentations. And we are recording this webinar, and it will be uploaded to the DLF YouTube channel after we are done, and we will not be recording the Q&A session. So without further ado, let me turn over first to Molly Bragg. Molly is the head of digital collections and curation services and the digital collections program manager at Duke University Libraries. So Molly is going to be sharing how Duke Libraries Digital Collections program collaborators use Jira and Confluence to manage their work. So over to you Molly. Thanks Marisa. I'm going to share my screen. Can everybody see my screen. Okay, good. Put it into slideshow. There we go. Hold on one second. Hello, as Marisa said my name is Molly Bragg, and I work at Duke University Libraries. Today, I'm going to talk with you a little bit about the context for our digital collections program just briefly and what we need from project management tools and then we're going to go into a demo of Jira and also Confluence. Alrighty. So first off, what is Jira and Confluence anyway? These are both products created by a company called Atlassian in Australia. They also own Trello if you have used Trello in the past. Jira is an application that was designed specifically for managing agile software development projects, but it's also just a really intense task management tool. So Confluence is a wiki and so you can create web pages and share them and things like that. There are a lot of integrations between the two products so in my experience I've always used them together, though you can license them separately, which I just found out today. But at Duke our digital collections program has three main goals, digitization, digital preservation, and online access to our collections. That's our URL at the bottom of the screen. Note that we do develop our digital repository and access platform ourselves and we use Jira as part of that work but I am not going to cover that today. I'm only going to talk about digitization project management. So many of you can imagine or have experience with our digital collections implementation group is distributed across different departments and different divisions within the university library. I think this is pretty common among digital collections programs, but it means that we need tools that we all have access to that we can all speak the same language on and that we can kind of dip in and out of. And I say that because a lot of the folks that I work with, they have other priorities, other work that they're managing. And so for their digital collections work they really just need to go straight to it and know exactly what they need to work on for that bit of time that they have for it. Sorry I keep hitting the wrong button on my keyboard. So we entered Jira. We started using Jira in 2016 2017 and the license, the purchase of it was really driven by our software development teams. However, once it arrived, I started using it with a couple other colleagues for digital collections. I want to note that we pay for a hosted version of Jira and Confluence so we don't host it ourselves but you can host it yourself. And we use Jira on the digital collections team for all all of our workflow work post scanning. So after something scanned the digitization digitization folks submit a ticket for ingest, and then we start managing the work through Jira so digital repository ingest description review metadata crosswalking permissions management, and then any configurations that are needed for the specific project that all happens with the team in Jira. So now I'm going to do a demo and walk you through you can still see my screen right. I'm just going to apologize in advance because I'm trying to move slowly and deliberately through the tool but I am probably going to be jumping around a little bit too. Alrighty. So here we are in Jira. This is my dashboard, which I've configured so every time I log in, I see this. As I mentioned, Jira is a really good task management tool. So, all of the various tasks are called issues in Jira vocabulary. And you can make different kinds of issues so an issue can be a task or a story, or a bug, or you can design your own kind of task as well. You can organize tasks into groupings called epics. And we use epics a lot. That's what you see on the right hand side of the screen, and I'm going to walk you through to epics today. Just a general note that you can do just a ton of customization on your Jira instance and your confluence instance that has like tons of fancy features also at kinds of bells and whistles. When I first started using Jira and Confluence, a colleague and I did a bunch of customized stuff because it was cool. But I found it really hard to maintain and so I was spending a lot of time managing Jira instead of my work. So I took a different tact and now I just do everything as simply and as out of the box as I can with Jira. So I did not use a lot of the fancy bells and whistles. Alright, so here we are again my Jira dashboard. We have a couple different groups in the library using Jira, and so they all have their own projects. And so that's what you're looking at now. We are going to stay in the digital collections project for today. I told you I use epics to organize my issues. So we're going to click on one specific epic. So we can see what that's like. This is the view of an epic. This epic is named for the specific project that we're working on with it. It's called Behind the Veil. It's a digitization project that's gone through many iterations since 2011. But with this view I get the epic itself and then I can see at a glance, all the issues that are associated with that epic. I can even see at the top right below where it says issues in this epic. This green bar is a progress bar. So it's green. That means I have this many done issues. And if you hover over it, it's 15 done, 5 in progress, and 10 yet to do. So for an overall rate of like 50%. So I'm 50% done with this epic apparently. You can see all the issues. As I said, there's the issue number, the issue name, and then you keep going over to the right and you've got the person it's assigned to and the status. So this view is really good for me because I can look at a glance and see, okay, these things are done. These things are in progress. These things are yet to be done. And from here I can change the status or assignee really easily. So this, this ticket down here launch video tapes. That doesn't have an assignee, but it's actually supposed to be mine. So I'm just going to assign it to myself right there. And now I've just gotten an email that says I've been assigned something. Let's look at a specific tickets. Click. There we go. So this is one specific issue or in this context it's one specific bit of work that has to be done for this project. In this case it's an ingest activity. So our digitization specialists when they're done digitizing files, they submit a ticket for it to be ingested and they include all this useful information about the files. So this is an ingest to our staff that does ingest. You can tag people in tickets, you can use attachments in issues, and then they've got these great comment threads. So, some of our comment threads get really long if people have questions or something looks bad. You can tag people in comments so here my colleague Medina assigned something to Maggie and tagged her Maggie got a notification. I can add other tickets to the comments and it renders dynamically which is pretty cool. So let's say I want to say something about this particular ticket. It pops up the issue number, the title and the status which is pretty cool. Is that all I wanted to say about that. Oh, also within a issue you can link different issues together pretty easily. You can also create sub tasks, which I didn't mean to do. You can create sub tasks so you can go from like the hierarchy of effects to tasks to sub tasks if you want to. I personally don't use sub tasks because I find they get lost. And so when we start using them, I always miss them, and then I don't get my work done, and my team gets annoyed. So that is the basics of issues, and this particular epic. This particular epic, as I said is organized around one project, and you can see that the issue titles are for the specific tasks associated with that project so we have ingest we have metadata. We have launch, all that stuff so that's one way that we organize our work in JIRA. This way the advantages of doing it this way is that if the project is really big like this one, then you can be working on different phases of the work. We also have some tandem so we've got in the in progress we've got a bunch of metadata going on, but we also have some launching, and we have some ingesting going on, and it's really good because sometimes our work isn't exactly linear. So this is is really good for this type of large sprawling project. So what we're going to use ethics is to organize them around specific services or workflows. So I'm going to show you a different epic. This is called DPC scanned patron requests folder level. And this is for our patron request service that we do with the Rubenstein Special Collections Library. Patrons can send us stuff that they need scanned. And we're also since right before the pandemic we started coming up with a workflow so we could ingest and provide access to those scans as well. And then the pandemic started and that's like all we did. And that's like all we've been doing for the past three years we've done, we've done some other stuff but it's been the majority of what we've been doing is this patron request workflow. And we just put all of those ingest requests and the associated work under one epic that is for that specific project type. This specific epic has over 500 issues associated with it. So there's so many issues that it actually doesn't display in your typical epic view. So Jira makes a nice little canned search for me that I can look at all my 509 issues from here. So there's obviously many, many, many issues on this view. But I can sort them, I can sort them by status, by assignee, things like that. And you can see where's the one I want to look at. Where'd it go? Nope, not that one, not that one. This one. Okay, sorry. So with these particular tickets, instead of having one ticket per activity, we just pass the ticket around. So there's the ingest information. But then you'll see in the comments. This one has a lot of other comments. But basically, we will pass the ticket from person to person as the work goes through the workflow and then we just make little comments. So here Maggie said, Hey, the metadata has been applied. And then I said to the next person, Hey, this is live put it on the finding aid. And then they did. And then I found an issue. So we just passed the ticket around basically and make little comments about our updates. And so for this specific workflow that works really well because if we were making tickets for every activity, we would make tickets all day long and there'd be four or five times as many tickets. So when you're looking at the issue, you can easily change the assignee over the right hand over on the right hand side of the screen and things like that. And you can see it's associated with this epic right there. Okay, let's go back to where we were. So again, like this view, I can easily sort. So here I'm looking at all the won't do and done. I can do by assignee. I can see that the search bar at the top of the screen changes as I click the different sorting options. This search bar is using the jury query language. So Jerry has its own query syntax so you can build your own complex query to slice and dice issues and get a different view of them. That's because you can put a lot of issues in JIRA. So we have a ton of issues across all projects. I just clicked on all issues. So if I don't want to use this JQL. I can also filter. So here let's do just things in digital collections that are tasks that are in progress. I can also just say what are all the in progress things that I'm supposed to be working on, and I can add myself. And now that I've gotten this view of all these things that I should be working on, I can actually save this as a filter. So that when I come next time. I can just click on that and know when I'm supposed to be working on. So that is really advantageous for my team members that come in and out of digital collections work. They can just come in and say like what's assigned to me and start working on that. And I have a couple saved. This is my other one for just the patron requests I'm supposed to be working on there's only seven right now. So I'm going to do this one more before the end of September. And yeah, so that's Jira there is, as you can see there's a lot of issues. It could be easy to get lost in there. And that's where Confluence comes in for my team. So here we are I just clicked over to Confluence which is a wiki. And it allows you to create web pages and organize them. If you click create Confluence actually has a whole bunch of templates that are pretty cool. A lot of them are designed around agile software development, but some of them could be repurposed to anything they have a project plan. This is a pretty great looking project plan that I think could be applicable to other projects. What I've done is I've created my own template. And what I do is every quarter I come in to Confluence and I create a list of all the projects that we should be working on in a particular quarter. So this is the quarter, April through June 2023. I have my little graph collections to launch, or I'm sorry my table collections to launch. And then each row is a priority project. I can embed that epic link from Jira and it displays dynamically. I can add some notes. For example, down here on the second row we've got a project listed and then it's got some notes like waiting for Aaron. Just a high level note. And then I embed these little charts that show you for each epic how many tickets there are and what status they're in. So, for that last quarter we were working on this one this Duke basketball films project and you can see there's 14 done issues and there were 14 total so we must have finished that one. Good job for us. So we've got all the ones we're going to try to finish in a quarter. And then at the bottom I've got ingest only. So these are ingest priorities if it's a really big or complicated project will spend more dedicated time just ingesting it. And this is just to keep my team focused on whatever work they're supposed to be working on in a particular quarter so they don't get lost in Jira and wonder what they're supposed to be working on. And it's really easy to make these charts. I think that's all I wanted to share with that so let me pop back to my slides. I want to talk about what works with our use of cheer and confidence. It turns out that a tool designed for task management is really good at it is very good to create to do is assign them to people and see how people are doing on them. It's an orderly priorities page that I set up and confluence and maintain those work really great for me for the team for our stakeholders I think I think those are successful. Another cool thing that I didn't cover in Jira that I really like, you know we have different groups working in different spaces within Jira, but because of the way they do epics and because of some of there's even some labeling options that we didn't look at either. It's really easy to tie issues together from across different projects. So if I have a digital collections project but somebody's doing a development project that relates to it. I can link them together in the same epic really easily which is cool. Oops, not done yet challenges. There we go. So it is price point and limits for our subscription. It's expensive. We pay for 100 users we pay, oh, pay something like $13,000 for both cheering confidence so it's really expensive. And we're limited by the number of users we started out with a much smaller account and we had to be really judicious about who could use it and the organization, which isn't great. So it's really hard to reserve, you know, even for me using trying to use all the out of the box features and not customize anything, it still takes a while to get used to. Also I showed you a little bit about searching and setting up views of different tickets. You can do a, you can do that in a lot of different ways, and sometimes it can get kind of confusing. And someone says I'm looking at this board, but you don't see the same issues that they see because you configured your board slightly differently. It can get kind of tricky that way. That's all things that can be overcome but it is a bit of a challenge. Okay, that's me I talked a lot. I'm sure we'll have time for questions but that's my contact information to thank you so much. Thank you. That was fantastic. So we will hold questions until the end of both presentations. So right now I'd like to introduce the lease Smith of leases the digital library project manager at the University of Southern California libraries, and she'll be sharing how the USC digital library team uses air table over to you release. Okay, let me show my screen. I should be looking hopefully at air table. Air table is a cloud based tool. That one's our cloud based tool that's basically a database in a spreadsheet view. And what I would like to show you in these 20 minutes is if you collaborate with a team and you're getting frustrated with Google sheets. It might be worth looking into your table. In the background, I'm the project manager for the digital library at USC. Back in 2019 I was manager of the digital imaging lab. And at that time we typically had two to three digitization projects at a time in the lab. And then we received a contract to digitize the archives of the Department of Defense and because of the huge scope of the project, juggling Google sheets just wasn't an option anymore. Since I don't have time to get too in depth, I just want to show a base that's pretty simple but very helpful. So this is the metadata tracking base. You can see that it looks like a spreadsheet but there are colors. This base is used to track everything that we that we put into our that we upload into our dams. So this first column is called batch identification, and this is the name of the folder that's been uploaded into the dams. This is the collection that it's a part of number of files within the folder, the name of the person who uploaded it, the date it was uploaded. This is the person who's going to do the metadata. And if metadata is completed, the date that the metadata has been completed. So it's pretty straightforward, pretty simple. And I created it this way on purpose because getting a buy-in from a team is always really difficult. So I just want to keep it as simple as possible. And this is what these columns are because it gets kind of cool. So batch identification is a long text field. And I'll show you an example of that. But long text is pretty cool. This is just my like to-do list. And I just, I'm in a tab where I'm looking at each project. And this is a, you can do rich text formatting so I can do like little checkboxes, bullet points, bold italics, whatever. There are lots of options, but that's what you can do with long text. This one, it looks like a little gray square. This links to another record. So this is how all the tables speak to one another. This one, you can see if I double click on it, it links to this table right here. So that means that they're trading information back and forth. And I'll go into that in just a second. This one's a number field and pretty straightforward. It just means you can only enter in a number. You can't put any letters in here, which is really good for keeping your data really clean. If I'm using this field for a formula, it's not going to give me errors because it's only numbers. Uploader, so this is a single select. They also have a multiple select option, but one upload is done by one person. So it's a single select and this is kind of nice for like a controlled vocabulary. So you can see that everybody has the name that they want to use. So you can go by your first name, you can go by your last name, but it keeps it really clean so you're not getting spelling errors. You're not getting someone who's going by their first name one day and their last name another day. And the date field cataloger is also a single select. There are lots of options for different types of fields that you can have and I don't have time to go into all of them, but there's some really cool stuff in there. So, another thing that makes this a lot better than a Google sheet or an Excel sheet is that you can see here that it says grid view. So there are a bunch of different views. Grid view is your default view. So if I send somebody the space to enter an information, this is the view that they see. And it again, super simple what information they need to put in. It's pretty straightforward. So you can create your own views. So you can see that they're collaborative views, which means like people can go in and put in filters and groupings different sorted different ways. So people have created their own there. You can see I have mine here. And I have mine sorted by hidden field. It's hidden in the grid view. So I only want to see it. Other people don't want to see it, but it's a every time a new row is created. It automatically enters a created field. So I like to sort by this. And then you can see that I have other fields that I care about that other people don't really care about, which is the fiscal year that it was staged the fiscal year that the metadata was created and what digitization project it links to. We also have an upload form, which is kind of like a jura ticket, but a little bit simplified. So it's just if we have someone like a faculty member who is doing a project and we want them to create their own metadata. Or they are uploading themselves into our dams, then they can fill this out. I can send this to them and see what it looks like. I can send this to them and they can enter in all that information and it will create a new row in our tracking sheet. Then we have personal views. So you can see Deb is my director. So I'll look into her view. And you can see that I don't have power. I can't go in and hide fields, filter groups or change colors. I can't move these fields around. They're locked in. So I can't go in and mess up her stuff. This is how she wants to view our metadata tracking base. And she's got a group. So she's grouping all the rows and entries by collection. So she can easily see, oh, advocate has, I don't know why it's not showing me, but it has like, oh, here are some. So it has like 20,594 in Anas. And we've only been doing this since 2016. So these numbers might look kind of weird, but it's because that's when we started tracking. So that's pretty cool. And then I have my own personal views here. You can see my little possum icon. So digitization tracking. I go in and I have a filter set up. So it's only showing me the rows for uploader is any of the digital images. And the digitization project is empty. So this is telling me that this someone uploaded who was a digital imager. So it was digitized by us. And I haven't assigned it to a project yet. So I can go in and say, okay, I know who did it. I know who uploaded it. And I know what collection is part of. So I know that it's part of our curricular expansion project. And if there were any rows in here, I know that it's like a to do for me. And then metadata tracking is sort of a similar idea where I have a filter set up where it's date cataloging completed is not empty. So that means the metadata person has gone in and said, okay, I've created metadata for this batch upload. And the meta data fiscal year, which is field I'm responsible for is empty. So I can look at these see that the data was completed and know that this is all metadata was created fiscal year 24. So I'll just go in and assign that tag to them and I'll show you why that's important in just a second. Okay, so all my two views are done. So I can go back to my grid view and go over to the collections table. So these are all of our collections. Our abbreviation full name batches that are part of this collection. And then how it does a file count of how many files have been uploaded. This is really helpful because the digital imagers sometimes will come in and say, okay, we got a patron request for Asian maps collection. What is the abbreviation that I want to use in the file name and it's all right here. You can see that some are empty, which just means it was added to the digital like last time was added to the digital library was prior to 2016. So it's actually empty. It's just empty because we haven't been tracking that far back. So this is pretty cool because this is links to another record. So this batches is linking to this grid view that I was just showing. And so this is saying these batches are part of this collection. And this roll up that looks like a little roll up. This is saying I'm counting the batches. I'm counting those fields in that grid view that I was showing you before. I'm counting the number of files and it's just doing a very simple sum of values. So I can see how many files for each collection have been uploaded. I can change my view to backlog. So how do we track your backlog? This is really, really helpful. So this is just a different view. You can see like different views have different things hidden depending on what I'm trying to look at. So I can see my files uploaded and then I can see my files catalog. So this is a roll up of my batches. So what has been entered into that Cortex upload catalog table and it's counting the number of files, but only the number of files where the date catalog completed is not empty. So that means someone has gone in and said this is the day that I completed the metadata. So if it's not empty, that means the metadata has been completed and it's just doing. Oopsie, I just turned it off. I'll have to redo that sum of values. Okay, so then this is a percent catalog. So this is a formula field where it's just showing me what percentage has been completed. Green is good, red is bad, gray is even worse. So it hasn't even started yet. And then I can see the count of just another formula field of count of how many files are currently in the backlog. And this is this is another table and this is pretty simple. It's using those tags that I was putting into for the digitization and it's saying what project and how much has been digitized per fiscal year. So I can see how this project we did a little bit in fiscal year 22 we dropped it fiscal year 23 and then we did a lot this fiscal year 24. So I can just sort of track our digitization numbers here. I want to show you really quickly. Another way that I use this another cool feature of air table is that it lets you create these interfaces so it's taking the data that I want from our base. And it's putting it all into something that I can show my associate dean to show him that like, hey we have a real problem here in the digital library and we need. We need another metadata specialist because our backlog is like big. So this is showing him it showing him that really high top level. Beautiful pastel colors. It makes it make sense without showing him a huge spreadsheet. So this is the file staged this fiscal year. These are how many files we put into our dams. This is metadata records created this fiscal year. Like. File stage versus metadata. Yeah. Files cataloged all time files currently in backlog so. Yeah we need a metadata specialist we don't need any more contract, you know grant funded positions we need a real full time metadata specialist. And then you have that sort of same information in a little pie chart. Here metadata created by fiscal year here. And then you can see our percentage complete for different collections. Here, so it's just taking that information and making it kind of like. Pretty so he can see it. And understand it really simply on just like a very high level. I also want to show really quickly I don't know how much time I have. We also use we have many different uses for air table. That was just our metadata, which is one of our most simple bases. We also use it for tracking digitization requests. So we have tickets for the digitization request. So there's like that. Something like this, but it's just for creating a patron request for something to come into the lab to be digitized. And so special collections will create those and send over materials. And so this is my interface that's just a high level view of patron requests and digitization requests. So I can get a very quick idea of like what's going on in the lab. We have four tickets that haven't started yet we have nine tickets in progress and we've completed 256. And then I can see like where each project is. And then I can go into individual tickets if I want to say, OK, we're waiting on patronage for these. This is the collection. This is the number of materials, some notes from the lab and just like basic information like that. So it's nice because I'm a visual person and it's just giving me the information I need in a very like easy to understand way. So yeah, that's our table. I had a lot of help setting up my first base. But if you know Google sheets, if you know Excel, it really helps and it's pretty easy and it's really good. I think for collaboration because there's you can see the only the information that you want to see. That's it. Thank you, Louise. That was great. So we do have some time for questions now. So let's go ahead and stop recording, please.