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Linked Infrastructure for Networked Cultural Scholarship

Human brains work through a vast web of interconnections, but the web that researchers increasingly use to understand human culture and history has few meaningful links. LINCS will create the conditions to think differently, with machines, about human culture in Canada.

LINCS serves Canadian researchers by interweaving data from fields including history, communication, music, performance, and literary studies to transform how we engage with culture online.

LINCS will enable deep contextualization and new ways of understanding, empowering researchers and the public with the means to engage more effectively with a vast array of digital cultural content.

LINCS collaborates with stewards of cultural data collections and development partners committed to exploring the potential of Linked Open Data to contribute to a better open knowledge ecology.

LINCS benefits from and contributes to Canada’s national network of expertise in research software development, research computing infrastructure, and research data management.

Linked Open Data for Canadian Cultural Research

LINCS is converting and interlinking Canadian cultural research datasets, making them accessible as Linked Open Data for the benefit of scholars and the public.

What

The LINCS infrastructure project will convert large datasets into an organized, interconnected, machine-processable set of resources for Canadian cultural research.

Why

LINCS aims to provide context for the cultural material that currently floats around online, interlink it, ground it in its sources, and help to make the World Wide Web a trusted resource for scholarly knowledge production.

Who

With a team of technical and domain experts, LINCS will allow Canadian scholars and partner institutions to play a significant role in the developing the Semantic Web.

Featured Tool

Nerve

The CWRC-Writer online editor now incorporates NERVE, the Named Entity Recognition and Vetting Environment, both within CWRC and on GitHub, where anyone with an account can check out its ability to recognize people, places and organizations, and let users refine the results and add Linked Open Data identifiers that get incorporated into the text markup. LINCS will be building on this interface for vetting more sophisticated results of natural language processing. Huma Zafar has updated the NERVE backend to produce an architecture that is modular, extensible, and will scale easily in our Kubernetes infrastructure. The new platform goes beyond just NER and Vetting, and has been named the NERVE Secure and Scalable Infrastructure, or NSSI (pronounced “Nessie”). Head over to the project wiki to learn more.

From Our Blog

Writing in Circles: From Beginner to Expert and Back Again

— Sam Peacock, LINCS undergraduate research assistant — As an English student, I was always told to keep my writing concise. Doing so was often easy because I could assume that the person reading my work would be an English scholar, so their expectations of my writing and the knowledge they brought to it would […]

  • Mar 8
  • LINCS Project
Stand-ups for Software Development

— Eason Liang, LINCS computer science co-op — When I began my first co-op placement, I had no idea how software development worked in a professional environment. Previously, my experience had only been in the classroom, where  my classmates and I developed software for assignments. When I moved into a professional context, I was exposed […]

  • Mar 3
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Marvels of API Communication: The Diffbot NLP Vetting Tool

— Mohammed Marzookh Farook & Ananya Rao, LINCS Junior Research Analysts — If you’ve ever listened in on a technical conversation between computer scientists, you might’ve heard them refer to something called an API. What exactly is an API? Let’s break it down. An application is any software that performs a distinct function. Microsoft Excel […]

  • Feb 24
  • LINCS Project
Development in Steps: Learning to Collaborate on a Technical Project

— Basil Yusuf, LINCS computer science co-op — LINCS is using ResearchSpace as a platform for exploring relationships in interlinked cultural datasets. With ResearchSpace, researchers can browse, search, and visualize data in the LINCS datastore. In summer 2022, I was part of a team that was developing new features for LINCS’s version of ResearchSpace. Our […]

  • Feb 15
  • LINCS Project
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