Retiring OrgRef
If you aren’t already aware of OrgRef, it’s an open dataset providing structured information about academic and research organizations worldwide. The team here at DataSalon built and launched it back in September 2014 as a […]
Data Integration & Cleansing
Looking back, planning ahead
At the start of the New Year it’s always good to reflect on some of the successes, changes and developments of the previous year. At DataSalon, 2017 was a ‘busy one’ and we were pleased […]
The magic of automatching
Over the last 10 years, we’ve been working with scholarly publishers to help them clean, link and de-dupe their institutional customers to create unique records from the many different ways customers are recorded in their […]
5 great ways to squeeze more juice out of your data
When you hear the phrase ‘data quality’, you may immediately think of fixing errors, and obviously that’s a fundamental part of improving the quality of your data. But there’s much more to a comprehensive data […]
Filters: the data quality Swiss Army knife
One of the issues we’ve come across in developing our new data quality tool is the sheer size of many of the data source tables. This makes a good method of filtering absolutely essential, both […]
Organization IDs: a new hope
A key part of the service we offer (through MasterVision) is helping publishers identify different versions of the same customer across various databases, and then joining those together into a single, unique record. This could mean untangling the […]
New Year, New Data
A big part of what publishers need to know about their customers is what content they are using or trying to access; and how much they are doing that. There are many reasons why you could […]
Data quality for the bewildered
Over the past year, we’ve been doing a lot of research & development into the challenges publishers face in relation to data quality, and working with publishers to address their real-world data issues. The word […]
Finding the potential in packages
A very common subscription model adopted by journal publishers is the bundling of titles together into packages/collections, often by subject or the age of the content. This provides libraries with economies of scale and access to […]
Auto-clean your way to quality data
As a publisher you’re not alone in suffering data quality headaches – in fact any busy organization capturing large volumes of customer data is likely to experience similar issues. Without careful maintenance, inconsistencies and inaccuracies […]
