This document discusses the in press checking process at a university library. It outlines the key steps in the process which include accepting works into the system, setting and removing embargoes, publishing works online, and providing customer service. Metrics are shown tracking the number of in press items over time. Plans for future improvements include automating more of the process, prioritizing items for updates, and simplifying documentation.
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Modifying the schema of a production database is hard. If something goes wrong, the impact on both customers and the team can be enormous. And it can be hard or even impossible to rollback a database schema change if things go wrong. And the same is true for any architectural change for a production application.
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Expand contract pattern continuous delivery and databasesLeena N
Modifying the schema of a production database is hard. If something goes wrong, the impact on both customers and the team can be enormous. And it can be hard or even impossible to rollback a database schema change if things go wrong. And the same is true for any architectural change for a production application.
The Branch by Abstraction and Strangler Pattern makes significant application changes easier. Are there any similar patterns we can use to make production database changes less risky?
Indeed, there are. The Expand/Collapse pattern is a blueprint for making the database migration and makes the remodelling both reversible and safe. By expanding the application to accommodate both the old and the new schemas in parallel, we can give ourselves time to:
- Migrate any downstream dependencies on the old database schema;
- Gain confidence that the migration is safe.
We contract the application to the new version, once we’ve satisfied that the old schema is no longer needed.
The pattern helps to make significant, but necessary refactorings to your data model in a continuous delivery way. Most importantly, without threatening the robustness of your production applications.
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Nimble Athena is an internal tool that enable us to provide insights and communicate with our clients via automated data collection from tools such as JIRA and PivotalTracker
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When you’re managing projects in Basecamp, there’s the common issue of attaching and then downloading files to view and edit documents from different team members, contractors, clients and freelancers.
We think that cloudHQ for SugarSync can greatly simplify asset and document management for Basecamp users. Just enable CloudHQ synchronization between Basecamp and SugarSync. And that’s it: set it and forget it.
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• Different migration patterns and why you may want to use these different methods
• How to prepare yourself for life after migration, which won't include updating your resume.
This presentation introduces Kicktag and the Cosmos reporting platform - this is the perfect place to start if you haven't worked with us before, and there are a number of references for further reading.
In this deck, we present an outline of the Cosmos platform including how the reporting modules and data integration tools work together. There are a number of visual examples ranging from basic document libraries to real-time analytics dashboards and bespoke mobile business discovery portals.
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2. In Press Checking
Accepted
• Compliance
• Access requirements
• Set embargoes
• Remove embargoes
Publishe
d online
• Stewardship
• Complete metadata
• Match version of record
• Customer service
6. Future plans
• Re-assess how web alerts information is collected, maintained, and
consulted (eg. proactively removing old/duplicate information; creating
a standalone, updatable web alerts spreadsheet)
• Further automate the generation of the bimonthly spreadsheet by
integrating macros where possible
• Improve the identification and prioritisation of items
most likely to require an update by introducing a
‘date last checked’ field in the repository
• Simplify and streamline the design of the bimonthly
spreadsheet for easier consultation by the team
7. Please do get in touch if you’d like to share what you do or
you’d like to know more about our in press processes!
Thanks!
Email: research@library.leeds.ac.uk
Phone: 0113 343 0583
Editor's Notes
Simon and I are part of the Research Support team based in the Edward Boyle Library at Leeds. Thanks must also go to our colleague Liv Bonli who looks after our in press process and has provided a lot of the information for this presentation.
I wanted to provide a bit of context to our team before Simon shows you the detail of some of our processes for in press checking. We are very lucky to be part of a big team of 17 people, including 10 who work on processing items in our repository. Of those 10 a number are part time and everyone has other tasks to do so it’s not 10 full time folk processing away. Still, we’re very grateful to have seen our team grow over the years from one person processing part time to the current team.
We are a Symplectic – EPrints institution. Our instance of EPrints as most of you will know is a consortial one shared with the Universities of Sheffield and York.
We have processed over 13500 unique items since the beginning of April 2016. Our aim is to make metadata and articles available as soon as we can to our users. Of course some of these items will actually be “processed” multiple times as we are able to add more comprehensive metadata when it becomes available. And it is this checking for updated metadata that brings us here today as we wanted to talk to you about the processes we use for checking in press items for updates.
In press checking is a workflow to identify and update items that were deposited and processed prior to publication, i.e. upon acceptance for publication or whilst published online early. There are two key reasons for undertaking this task, namely to set embargoes in order to fulfil the access requirements of the REF 2021 open access (OA) policy and complete the bibliographic metadata of papers in our repository. Since 1 April 2016, we have checked 16229 papers of which 6906 were updated, a success-rate of approximately forty-two percent.
Prior to 2015, this was an ad hoc task that relied on manual checking and occasional emails from authors to request an update to a deposited item. Since then, the process has evolved gradually to incorporate new techniques. This development has necessarily been shaped by the need to make sure that University of Leeds research outputs comply with the OA requirements. The needs of researchers has, however, been another significant influence because the data in Symplectic Elements is feed to the departmental websites, where it is used to populate the publication lists on staff profile pages.
Under our current process, we generate a new spreadsheet every fortnight that draws upon data from bibliographic databases, data from our systems and standardised notes that we have included in the metadata in order to prioritise the checking of items that are at risk of non-compliance or are likely to be awaiting an update. The checks performed and resources utilised include:
Web alerts from Scopus and Web of Science. We use the Fuzzy Lookup Add-in for Excel (https://www.microsoft.com/en-gb/download/details.aspx?id=15011) to compare the alerts received against the accepted and published online status items in the repository.
Comparison of data from our CRIS (Symplectic Elements) and institutional repository (ePrints) to identify records harvested upon publication by Elements that have a later publication status than the repository record. This data is provided to us as a report.
Administrative metadata provides us with information about the embargo to be applied upon publication and the date when an item was last checked. We add standardised notes to the review comments field in ePrints, e.g ‘0 month embargo’ and ‘IP Checked yyyy-MM-dd’.
CrossRef API to search for the title of each accepted status item in the repository. Potential updates are identified by exact and fuzzy matching of the results before using any DOIs yielded for checking. This has been an occasional process.
Today, we will focus on a new process that we introduced in June 2018. It uses an API call to check identify published online status items in the repository have a volume assigned to them and thus appear to be fully published in the CrossRef database. We would like to share it with you because it is:
Quick
Easy to replicate
Effective/accurate.
We start by populating a spreadsheet in Excel with the bibliographic details of the published online status items that are going to be checked. The only essential metadata field is the DOI, which is used in the API call to find the appropriate CrossRef data against which we compare our repository record. In the illustrative spreadsheet screenshot, there are two groups of publications at the top of the page that were identified during some of the checks described previously and prioritised accordingly. The items shaded in orange are those with a harvested Symplectic record that indicates the work is now at a more published status than our repository record and those in green have no embargo from publication. The latter need to be revisited to make the fulltext available within one month of publication (i.e. the end of the embargo) in order to be REF OA policy compliant.
Using the WEBSERVICE function and a formula to incorporate the DOI in to a URL string, we can retrieve metadata from the CrossRef API that will indicate whether or not the item is now published. We have been fetching the volume number, which acts as a proxy for published, based on the premise that volume numbers, generally, are assigned at the point of final publication and the absence of a volume number suggests that it is still online early. It works by matching the doi from the spreadsheet with the appropriate CrossRef record, selecting the specified metadata fields and returning them in JSON format. Conditional formatting can be applied to highlight the cells in which the JSON data includes a string containing “volume”. The highlighted cells can be checked and updated as published.
This process has helped us focus our attention on those items that are ready to be updated rather than working through a list and checking everything that has not been flagged as a potential update by any of our in press checks. We have utilised it in the last four in press reports; 378 potential updates were identified and checked of which 372 (98%) updated.
The impact is clearly visible in the line graph; the total number of remaining in press items (orange) and quantity of remaining published online items (green) both started to decline following the introduction of this process.
By August 2018, we had reduce the number of accepted and published online items to 1,386 from just over 2000 at the start of the year. We reached our all time high of 2,112 in press items during February 2018, which was the period when we were training the new members of the repository team. Despite our recent progress, we still have some 400 more items in the repository with an accepted or published online status than we had at the start of the REF OA policy.
If we can continue to identify the items that require an update, it will help us to direct our efforts appropriately and such efficiency can free up time for other tasks. We intend to take a step back to examine our in press process and remove inefficiencies but there are still ongoing challenges including:
Identifying items that are not indexed by databases
Reducing unnecessary repeat checking
Ensuring that deposits are compliant with the REF OA policy whilst not neglecting out-of-scope material.
Refinements to process have had big impact on reducing amount of redundant work
Not an exact science
Constantly evolving
We have identified some of the specific changes to further improve our efficiency that we are looking at for possible future implementation. These include:
Separating out Web Alerts doc (standalone doc that could be referenced, rather than duplicated each time)
Removing more old/duplicate web alerts (to speed up process)
Integration of macros where possible (i.e. for generating report)
Date last checked: possibly a field in WRRO, or better ways of identifying via review comments
Consolidating ‘friendly’ version (i.e. In Press spreadsheet) into single tab.
We’re really interested to hear what other people are doing in this area so please let us know what you’re doing.