8 posts tagged with "Technical"

The Problem​

Documentation is an integral part of all software products, and for it to be useful, it must be comprehensive and detailed. However, this presents a challenge for both users and developers. Users, especially those who are newcomers to the software, can find it daunting to sift through large blocks of text, while developers often struggle to make documentation appealing and digestible.

Throughout university, I have been in the former category. As a user, I have always found documentation difficult to grasp. It often left me with more questions than answers. It especially did not help that the documentation websites I used often had terrible navigation and few resources to help me grasp what I was reading, leaving me scouring through various sites to find information that was tucked away in some hidden corner.

As a co-op student with LINCS, I was tasked with migrating the Canadian Writing Research Collaboratory (CWRC) documentation site. This website provided information about and access to the three ontologies developed by the CWRC, each with its own set of documentation. This had me worried, because how could I develop a website that could display documentation effectively while taking into consideration navigation, aesthetics, and page layouts?

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 team was a collaboration between contributors with a background in user experience (UX) and contributors with a background in software development. We worked in tandem: the UX group recommended features to improve the experience of using the web application. These recommendations were turned into tickets in GitLab. The tickets described what the desired end product would be, and it was up to the developers to determine how to achieve this goal. The development lead shared tickets out among the software developers, dividing them up based on what would be required to build the suggested features...

If you’ve ever listened in on a technical conversation between computer scientists, you might’ve heard them refer to something called an Application Programming Interface (API). What exactly is an API? Let’s break it down...

When beginning my very first co-op job search, I had no idea what employers would expect from me. It was a daunting task looking through the job postings and deciding what I thought I’d be (somewhat) qualified for. After a few job interviews, I applied to join the LINCS project, feeling confident that my skills aligned with the job requirements. Eventually, I was offered and accepted a job from LINCS, beginning a journey that has challenged my technical abilities every day and has expanded far past what I originally thought I’d be doing...

“Most people make the mistake of thinking design is what it looks like. People think it’s this veneer—that the designers are handed this box and told, ‘Make it look good!’ That’s not what we think design is. It’s not just what it looks like and feels like. Design is how it works.” - Steve Jobs

If you are a developer, designer, or a creative individual interested in design, you are probably familiar with the phrase “good design is invisible.” Everything is designed—there is thought behind every project or product—but only a few things are designed well. When design is done poorly everyone tends to notice its flaws, but when design is done well it usually goes unnoticed...

In data science there is a commonly used process called Extract-Transform-Load (ETL). ETL involves three main steps:

1. Extract data from a source,
2. Transform the data via data cleansing and data manipulation, and
3. Load the transformed data to a data warehouse (the final collection of data) (Sethi, 2018)

Before having much experience in data processing, my colleague Devon and I were not sure what ETL was. Now, after jointly transforming an entire dataset from XML to a whole new structure utilizing triples using CIDOC CRM, we’re beginning to understand the process...

As a Cyberinfrastructure project funded by the Canada Foundation for Innovation, LINCS is building its infrastructure on the resources of Compute Canada which operates a Cloud service run with OpenStack.

Cinder is the default volume storage provider for virtual machines provisioned on the OpenStack platform of Compute Canada. It is the last layer of a complex multi-tenant system that abstracts Ceph storage and hypervisors on top of hard disk drives. It is, however, the closest you can get to the network-attached storage (NAS) system of Compute Canada...

There are many graph databases out there that support Resource Description Framework (RDF): Virtuoso, GraphDB, Stardog, AnzoGraph, and RDFox, to name just a few popular ones. But if the requirements for your triplestore include open source, as it does for our CFI funded LINCS project, then Blazegraph and Apache’s Jena Fuseki are two of your most mature options...