Noah’s End Of Year Reflection

Hello! I joined the DHAs in January of this year and over the past 5 months, I have learned so much and gotten much-needed experience working in a professional setting where more was expected of me. This has been a great experience and I am glad I got to do it with such nice people. There were a ton of things I learned with the DHAs and a lot I know I can grow from.

Firstly, learning how to communicate formally and do that well. Never in my prior work experiences did I have to connect with professors and other students. While it may be intuitive for others, I found it challenging to send formal emails and also follow up with them and keep communication strong. I got to teach a class of mostly seniors WordPress when I had only started learning how to use it a few months prior. I was extremely nervous, and although I personally thought I could have done better, according to Em I did a good job. I also learned how to communicate with my coworkers too. Throughout my time here, I worked on projects mainly with other DHAs or on projects overseen by my supervisors. I learned to ask questions whenever I got stuck instead of trying to overcome it stubbornly and to continuously check in with my team members – particularly when it came to working on the CARCAS project. The CARCAS project was what I spent most of my time working on with Erin and centered around uploading and maintaining 3D scans of various carcasses on the CARCAS website.

Screenshot of the poster-script I wrote for CARCAS using Node.js and Puppeteer running locally.

Another skill I got from working with the DHAs was how to learn new technologies quickly. Git, Conda Environments, Node Scripts, Puppeteer, DataLad, Model-Viewer and WordPress are just some of the technologies I had to learn on the fly while working with the DHAs. At first, I had a lot of trouble reading documentation, and trying to learn so many new technologies and applying them on such large projects like CARCAS. However, I got much better at it, and in my other classes like CS 347, I start to realize that part of being a great Computer Scientist is being able to learn new technologies quickly – as technology is always advancing. The skill of learning new technologies is definitely not something I have mastered yet – particularly with reading large volumes of documentation – but is something I definitely can say that I got better at; and being with the DHAs definitely made me realize the importance of it.

Finally, another skill that I can say I learned is how to manage time effectively. The work with the DHAs was very independent. We would choose a task and it was up to us to take the necessary steps to get the task done. Em or Austin never would remind me to do something at a certain time, it would all be on me. This requires a lot of self-control and responsibility to make sure I send the emails to the right people on time or take the necessary steps to get the poster script on the server by a certain date. I also had to balence working with the DHAs while taking up a lot of high level classes this term. I had to learn to say I was too busy when offered a task – which was something I used to find difficult – especially at the start of my time here where I would accept any and all tasks presented to me.

Unfortunately, with the swim season starting again next fall and me taking even more difficult classes next term, I will be making the apt decision to step back from the DHAs for the time being as I focus on my academics and the swim season. Being a DHA has been a wonderful experience that I will forever be grateful for as my first comprehensive work experience and I look forward to working with the DHAs in the future.

Goodbye for now!

Gale Digital Scholar Lab and Constellate: A Comparison

In previous blogs, I have discussed how Gale Digital Scholar Lab (GDSL) can be utilized to create datasets and subsequently conduct various analyses on them. Recently, a comparable online ‘data lab’ has emerged as a contender: JSTOR’s Constellate. Much like GDSL, Constellate is an online platform, developed by JSTOR, designed to support digital scholarship by providing tools for text and data mining across a broad range of academic content. Researchers, data scientists, and advanced students can utilize Constellate to analyze and explore diverse datasets, conduct advanced text analysis, and gain insights from academic texts. The platform offers a suite of tools for tasks like clustering, n-grams, and topic modeling, and integrates with Jupyter Notebooks for users who prefer coding in Python or R.

In this blog, I intend to explore the distinctions between Constellate and GDSL, highlighting how each platform may be better suited for different purposes. I will assess them based on various criteria, including the quality of the database, access to full-text content, user-friendliness, and flexibility.

1. Quality of Database:

Both tools provide researchers with access to a database containing a wealth of materials. In the case of GDSL, this database comprises a diverse array of, in many cases, public domain content, ranging from historical newspapers and magazines to flyers and other ephemera. It is worth noting that the Gale database includes more academic sources alongside its ‘non-academic materials’. This incorporation of academic works into its database creates a blend of both academic and non-academic materials. This rich variety of content makes GDSL’s database an extensive resource for researchers seeking a broad spectrum of information for their analyses and studies.

Constellate employs the formidable database of JSTOR, esteemed for its comprehensive coverage of academic journals and papers across numerous disciplines, with particular strength in the humanities. This expansive repository offers researchers access to a wealth of scholarly literature, providing authoritative sources and profound insights for academic inquiries in fields ranging from history and literature to sociology and anthropology. While Constellate’s focus on academic content may mean it features fewer non-academic sources compared to GDSL, its emphasis on scholarly rigor and depth of coverage makes it an indispensable tool for researchers seeking to explore and analyze academic research, especially in the humanities.

Researchers seeking a combination of academic and non-academic content can benefit from using Gale Digital Scholar Lab (GDSL), which provides access to a diverse range of materials including historical newspapers, magazines, and other non-academic sources alongside academic works. On the other hand, for those focused solely on scholarly content, Constellate, with its extensive collection of academic journals and papers sourced from JSTOR, serves as an excellent resource. By understanding their specific research needs and preferences, researchers can choose the platform that best aligns with their objectives and maximizes the efficiency and effectiveness of their research endeavors.

2. Full-text Access:

While both Gale Digital Scholar Lab (GDSL) and Constellate offer general access to their respective databases, a notable distinction lies in their policies regarding full-text access. GDSL grants users unrestricted access to the full text of the content within its database, enabling researchers to delve deeply into the materials and conduct thorough analyses without constraints. This unrestricted access is particularly advantageous for users who require comprehensive access to the entirety of the available dataset for their research endeavors.

In contrast, Constellate adopts a different approach regarding full-text access. While users have general access to the datasets generated by Constellate, including metadata and select text snippets, full access to the complete text may not be readily available. Instead, researchers interested in accessing the full text of the datasets need to submit a special request. This additional step is likely implemented to adhere to copyright regulations and licensing agreements, especially concerning the academic content sourced from JSTOR. Consequently, Constellate’s approach to full-text access may involve a more structured process, potentially requiring users to navigate copyright considerations before gaining complete access to the textual content.

This disparity in full-text access reflects the differing compositions of the databases maintained by GDSL and Constellate. GDSL benefits from a substantial amount of public domain content, contributing to its ability to provide unrestricted access to the full text of the materials. On the other hand, Constellate’s database primarily comprises academic content sourced from JSTOR, necessitating careful consideration of copyright and licensing restrictions. A researcher must keep this key difference into account when making any decision about which tool to use.

3. User-friendliness:

Gale Digital Scholar Lab (GDSL) distinguishes itself with its abundance of automatic features and user-friendly interface, catering to researchers who prioritize ease of use and efficiency in their digital scholarship endeavors. GDSL’s suite of automatic features streamlines various aspects of text analysis, from data preprocessing to visualization, minimizing the need for manual intervention and technical expertise. This automated approach empowers researchers to focus on their analyses and interpretations without being bogged down by the intricacies of the tool itself. Additionally, GDSL’s intuitive interface further enhances user experience, making it accessible even to those with limited technical background or experience in digital scholarship.

In contrast, Constellate, with its reliance on programming and integration with tools like Jupyter Notebooks, presents a more complex environment suited for users comfortable with coding and advanced analytical techniques. While Constellate offers unparalleled flexibility and customization options through its programming capabilities, including the ability to write and execute code in Python and R, it may pose a steeper learning curve for researchers less familiar with programming languages or text analysis methodologies. However, for users proficient in coding and seeking sophisticated analytical capabilities, Constellate’s complexity provides a powerful platform for conducting advanced research and exploring complex datasets in depth.

Ultimately, the choice between GDSL and Constellate depends on the specific needs and preferences of researchers, as well as their level of technical expertise and familiarity with digital scholarship tools. GDSL’s automatic features and user-friendly interface make it an excellent choice for researchers prioritizing ease of use and efficiency, while Constellate’s advanced capabilities cater to users seeking greater flexibility and customization in their text analysis workflows, albeit with a higher degree of complexity.

4. Flexibility:

Constellate offers researchers significantly higher flexibility through its integration with programming environments like Jupyter Notebooks, empowering users to customize their analyses to suit their specific research needs. The ability to write and execute code in languages such as Python and R provides researchers with unparalleled control over their analytical processes, enabling them to implement advanced algorithms, develop bespoke visualizations, and explore complex datasets with precision and depth.

Moreover, Constellate facilitates transparency and reproducibility in research by allowing users to document and share the exact data or textual analyses performed within the platform. Researchers can provide detailed explanations of their methodologies, including the specific code used for data manipulation, analysis, and visualization, thereby enhancing the integrity and reliability of their findings. Additionally, Constellate enables users to share datasets fully, promoting collaboration and facilitating the replication of analyses by other researchers.

In contrast, while Gale Digital Scholar Lab (GDSL) offers a user-friendly environment for text analysis, its capabilities for customization and sharing are more limited compared to Constellate. GDSL’s focus on providing pre-built tools and workflows may constrain researchers who require greater flexibility or wish to document and share their analyses comprehensively. As a result, researchers seeking maximum control over their analytical processes, along with transparency and reproducibility in their research, may find Constellate to be the preferred platform.


In conclusion, Gale Digital Scholar Lab (GDSL) and Constellate each offer unique strengths and cater to distinct user needs within the realm of digital scholarship. GDSL stands out as an excellent tool for beginners and researchers seeking to explore historical newspapers and other non-academic sources with ease. Its user-friendly interface and pre-built tools make it accessible to those new to digital scholarship, while also providing valuable resources for uncovering insights from diverse materials. On the other hand, Constellate emerges as a powerful platform tailored for users interested in humanities research and academic scholarship. With its integration of JSTOR’s extensive academic database and support for programming, Constellate provides unparalleled flexibility and depth for conducting advanced textual analyses and exploring scholarly literature. Researchers seeking to delve deeply into academic research and enhance transparency and reproducibility in their work will find Constellate to be an invaluable resource. Ultimately, the choice between GDSL and Constellate depends on the specific objectives and preferences of the researcher, with both platforms offering valuable tools and resources to support digital scholarship in their respective domains.