Sieve is a multimedia inspiration engine.
To give others a brief summary of the idea and its goals, Sieve is similar to existing social media and content aggregation services (I see it as being most similar to Tumblr) but it:
Tumblr Isolate image browser
Sieve aspires to serve as a feed for content aggregation and exploration, removing unnecessary distractions from other platforms while collecting and displaying their content.
It allows for the viewing of other social media and content platforms in one place from a variety of mediums – video, audio, pictoral, and written.
It provides multiple views conducive to each type of content to enhance the exploratory experience, and allows for saving types of content for later as well as publishing such content to your own
At first, this engine that will be self-hosted, and the self-hosted instance will independently generate content best for you provided links to follow.
To improve usability, this may extend to a service in which users can create their own workspaces and subscribe to the feeds of others ('meta-feeds'), though the focus of this project is to provide a variety of different ways to customize and display content.
Operationally, Sieve is an RSS feed reader – but one that puts multimedia content first. It can be provided feeds and can crawl the internet for topics similar to those already in feeds via a web crawler and content aggregation system.
The innovation here is the multiple views of content it provides – while attribution is important, other aspects of social content publication can be distracting or addicting. Sieve doesn't have 'likes', 'follows', or 'comments' – it seeks only to provide different ways of viewing the content we already interact with on other platforms.
On the back end, Sieve scans each of the feeds a user follows to find a cohesive 'theme' or 'style' from the content it displays, and prioritizes displaying more of the content a user saves. It does not track you or learn from you in any other way.
Sieve is minimal first. No clutter. It puts the content first and hides all excess information, allowing for 'focused' inspiration without potential distractions.
Previous efforts with seamless, content-first design include Archillect. This project seeks to avoid creating a new Tumblr, Instagram or Facebook – those platforms have become too bloated and interaction-driven.
This platform seeks to minimize interaction with other users and instead prioritize interaction with their content.
These distractions are deliberately obfuscated, hidden behind menus and obscured by a minimal interface – the content itself. There are no notifications, no numbers, no flashing visual cues to indicate additional information, as these are flaws that all make social media content more addictive. It's as simple as visiting a page and viewing content catered to the user.
The image view presents itself as a multipanel scrolling feed of image-based content. This scrolling can be infinite or paginated. I'll likely implement the latter first. Images can be clicked to open a larger view of the image and to view attribution if available.
This is probably the trickiest to get right; it may end up being an image view with GIFs instead of just images, but that would disparage any audio content that the videos may contain.
The information density of audio in videos is much worse than audio in isolation, so playing audio may not be relevant to the content, but providing a distraction free way to consume this content feels necessary.
This view will be similar to the 'theatre mode' that many services already provide, showing an oversized album cover while playing a specific song.
It'll focus on playing previews of songs rather than their entire contents so that the media can be set aside and continue to be consumed on another platform.
RSS is overwhelming and often doesn't present the information you're interested in – even good writers are bad at summarizing their own content and prioritizing the information that readers want, and often blogs address a variety of topics rather than focusing on a subset of articles that a specific reader may be interested in reading.
As such, the article view aims to do a few things that other services currently do not accomplish:
These articles will be viewable through a 'reader view' that the article view provides.
Advanced features for the article view include saving individual passages as opposed to entire articles.
In addition to sorting based on type of media, users should be able to identify categories that they're interested in. These categories are used by the recommendation algorithm under the hood and content is tagged with one or more of these categories when it enters Sieve.
This operates identically to the inspiration views, but it only shows content you've already saved.
I have several adjacent ideas that, while outside the scope of this project, could be added in the future.
I believe this project to be a viable product.
The open-source version will be provided entirely for free, and will provide the Sieve engine. No user accounts, following, liking, etc. will be involved with this draft (federation might be cool in the far future but it's by no means necessary). However, people will be able to try out and use the service on an individual basis by hosting it themselves.
The commercial features:
https://github.com/RSS-Bridge/rss-bridge bibliogram for subscribing to instagram invidio for youtube https://github.com/avencera/fast_rss for parsing rss from elixir backend https://github.com/miniflux/miniflux feed reader with Go https://github.com/zserge/headline ascetic RSS reader without server. 4kb and beautiful, works offline
Sieve's search shouldn't help users find whatever they'd like; rather, it should fuel and filter the existing results, similar to wrapping a comonad. - what does this mean
someone tweeted about rss rewind, where you're able to replay feeds day by day to trace the news, articles, etc chronologically what's in your rss feed interviews!
https://github.com/seenaburns/isolate/blob/master/README.md lighteeight tool for viewing art inspiration
https://memory-metadata.livia-foldes.com/ navigating the metadata of memories we save and share