“Vague, but exciting”
It's a famous reaction for those of us who cut our teeth on the Web and its history. It's also a reaction we have heard before about linked data for libraries.
We love this quote because “vague, but exciting” was how Mike Sendall summed up his then employee Tim Berners-Lee's “Information Management: A proposal” in March of 1989. “Vague but exciting…” was essentially the green light for Berners-Lee to continue working on his project, which became the World Wide Web. The following year, Berners-Lee and his tiny team wrote the first versions HTTP and HTML, built the first server and browser, and went live. Twenty years after his initial proposal was greenlit, Tim's 2009 TED Talk urges us to unlock our data and reframe the way we use it.
We’re heeding his call by advocating for libraries to expose their catalog records to the Web.
The Libhub Initiative’s purpose is to fuel that same excitement while fleshing out the details, in particular for Libraries and the use of Linked Data.
The videos, articles, and posts here on the Libhub.org site will demystify the process behind how libraries expose their catalog records to the Web. As you learn more and the process becomes less vague, you will become familiar with linked data, BIBFRAME, bibfra.me, Resource Description Framework, and more. The Libhub Initiative strives to explain these concepts in the context of solving problems, enabling discovery (and the use and re-use of information), and achieving goals.
Get involved individually and/or as a library system by doing something as simple as watching Tim Berners-Lee’s TED Talk. Here are three more easy entry points.
Engage with your vendors and service providers. Atlas Systems, Innovative Interfaces, and SirsiDynix are Libhub Initiative Sponsors and are committed to increasing library visibility on the Web. Talk to them and any vendors/providers you have about your interest in exposing your local assets to the Web.
Start thinking through your local data and special collections: for instance, its current formats; the size of your MARC-based data set; the type(s) of material you have; the authorities you’re using – there’s more, but it’s down the road.