Created on 2024-05-03 23:36
Published on 2024-05-04 04:00
Today’s internet and web environment heavily favors quick interactions such as liking and sharing, with only occasional bookmarking. Unfortunately, these actions seldom promote deep engagement with content that facilitates knowledge retention for future use and recall. Interestingly, I recently conducted informal polls on both Twitter and LinkedIn that reinforced a long-held suspicion: most of us never learned how to take notes effectively in a formal setting.
But isn’t bookmarking a form of notetaking, aimed at future reuse and recall?
Relying solely on bookmarking is not sufficient, as it typically results in just a link and some descriptive text that are not easily searchable or locatable, either locally or through a service provider. Even without these limitations, the utility of bookmarking is limited because effective notetaking should encompass a mix of:
Questions & Answers
Defined Term Sets (Glossaries)
How-Tos
References
Modern LLM-based conversational chatbots can serve as potent note-taking tools thanks to their advanced text processing capabilities. They become even more powerful when seamlessly integrated with other tools that facilitate the uploading of content to knowledge bases.
The newest version of the OpenLink Structured Data Sniffer (OSDS), a browser extension, enhances content interaction through conversational interfaces from various chatbots, including OpenAI’s ChatGPT, Mistral, Microsoft CoPilot, Google Gemini, Perplexity AI, Anthropic’s Claude, and HuggingFace Chat.
The process is straightforward once OSDS is installed and your chatbot interface preference is configured, as per the following steps:
Open the page of interest by clicking on its link (i.e., Web Address/Location).
Click the OSDS icon in your browser’s toolbar to generate a prompt for your preferred chatbot (for this example I’ve chosen ChatGPT via the OpenLink Personal Assistant [OPAL] interface).
Process the prompt.
Export the response to your knowledge base.
Repeat as needed.
In this scenario, notes are transformed into an entity relationship graph, constructed from hyperlinks to form a navigable Knowledge Graph for both humans and machines. This graph is then saved to either a DBMS or filesystem storage.
Thanks to the OSDS injected structured data format drop-down, you can effortlessly extract notes generated by OPAL and save them to a DBMS using a query service endpoint, such as a SPARQL endpoint, offered by our Virtuoso platform.
If desired, you can transfer notes generated through OPAL (or any other supported LLM-based chatbot interface) directly to a Personal Data Space or Pod. This is essentially an HTTP-accessible filesystem consisting of files and folders. Our Virtuoso platform not only supports this capability but also enhances it by integrating with the WebDAV open standard. Furthermore, Virtuoso can map one of these folders to its underlying Knowledge Graph storage, allowing for the use of familiar file saving patterns for storing notes.
Note: After successful authentication in OSDS, depending on the chosen authentication protocol, the system retrieves the operator’s profile document to check for preferences, such as the preferred storage location. If this lookup is successful, OSDS will utilize the discovered settings to establish the default target URL for uploading notes.
We are at a pivotal moment in the software industry, driven by advancements in artificial intelligence (AI). The integration of LLM-based conversational interfaces with application functionality is transforming the traditionally tedious task of note-taking into a highly productive activity.
As AI increasingly permeates our computing experiences, it’s crucial to recognize the role of knowledge creation, discovery, and management. Understanding these elements is essential for maintaining control as the sophistication of tool intelligence continues to evolve.