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The project aims to enhance user engagement and system communication in OpenELIS by implementing a robust notification system. The project will focus on creating a service worker for background execution, integrating the Web Push API for subscribing to notifications, and utilizing VAPID keys for secure communication between frontend and backend. The backend will be equipped with REST APIs to handle push notification events efficiently, ensuring seamless data exchange across the system. This project will significantly improve user experience and system-wide notifications within OpenELIS

<p>Sugar Dashboard, a user dashboard which shows user information like last activity opened, last project opened, activities installed on your device, most used activity, and visualizing them by heat maps and graphs.</p> <p>The Tamagotchi widget will replace the existing XO icon on the center of Sugar Dashboard. It will change its shape according to disk space, battery percentage etc.</p> <p>The last part is to create a journal like activity. The current Journal can not be extended/modified by the end user without making changes to core Sugar. This activity will be similar to the Journal activity, but can be modified by a user who wants to make changes. This part might also include integration of Portfolio activity which currently uses Journal objects.</p>

<p>With ccNetViz, this large graph render library using WebGL, I'll add edge animations on it. Including color animations, speed control and other fancy animations like wavy curve, dotted line and liquid fluid effects.</p> <p>These animations will be totally customizable and we'll also offer some high quality presets for user to choose.</p> <p>Finally, documentation for edge animation will be complete and we'll also have a demo page to show all function of edge animation.</p>

The goal of this project is to enhance the usability of Decorator Command Set (DCS) data by developing a utility/method to convert verbose, complex JSON formats into a more human readable YAML representation and back again. Currently, it is highly verbose to read, write, and edit DCS JSON files. The plan is to implement a converter that turns DCS JSON objects into a simple YAML format and back again. The new YAML will be less verbose and more readable, helping people work with DCS better. By the end, a fully integrated converter will be delivered, complete with tests and proper documentation.

MusicBrainz database sees a lot of edits made on a daily basis. Tens of thousands of edits. That’s a large number. With each edit, there’s associated an edit note which provides additional information about the edit. Often, these edit notes, as well as some edits, contain external links, which we want to archive in the Internet Archive. This project idea aims at creating a Rust application that can archive the external URLs using Wayback Machine APIs.

<p>The goal of this project would be to develop a web based user interface to visualise the variant prediction data from VEP plugin using the neXtProt tools to make it easily accessible to the users. The interface would be designed in such a way that it is performant, scalable and can easily handle large amounts of data that is computed by the VEP plugin API.</p>

This will be the Genome Nexus' cli to rule them all. Main objectives: 1. All 3 projects will be merged into one Java project. 2. Interface will follow Command Line Interface Guidelines to the point. 3. I will try to stick to Test Driven Design as much as possible. 4. A dependency will only be added to the project when it is unavoidable. 5. Killer cli documentation and web-based documentation will be added.

Genomic data sharing is slowed by manually cross-checking consent and data-use language against dense GA4GH and related policy text, while generic LLMs risk hallucinated citations. This project extends GA4GH-RegBot, an open-source RAG assistant that ingests policy PDFs into a Chroma vector store with a BM25 manifest, retrieves with dense embeddings plus BM25 fused via reciprocal rank fusion, and generates structured compliance JSON with hard grounding: chunk-ID allow-list verification with automatic retries and token-overlap filtering on the LLM path. Deliverables across the GSoC period include hierarchy-aware parsing and richer metadata for GA4GH PDFs, cross-encoder re-ranking on top of the existing hybrid stack, an open-source LLM path alongside the current OpenAI integration, Streamlit and CLI updates, Ragas or TruLens-based evaluation with documented thresholds, expanded tests and CI, and polished documentation for contributors and REWS stakeholders.

This project aims to enhance the search capabilities within the OpenELIS system, particularly the Search Patient module, providing users with a more efficient way of retrieving patient information. We aim to integrate a Java search engine library Hibernate Search with an Apache Lucene backend, to index key columns such as patient ID, patient name and other relevant data, providing users a faster way to search results. This will also include the integration of fuzzy search capabilities which will allow for approximate matching based on similarity, wildcard search which will allow for specified pattern matching and range search which will allow for searching for values within a specified range.

OncoKB™ is a crucial resource which provides comprehensive information about genomic alterations in cancer. However, despite the availability of APIs and annotation tools, some users, especially those without computational backgrounds, face challenges in effectively annotating variants and generating reports. To bridge this gap, my project seeks to publish a standalone npm package for visualization of OncoKB annotations and a report generation module to make the annotations downloadable by the users. Seamless integration of these modules with cBioPortal will mark the end of my project.

<p>A major need in cancer research is the development of non-invasive cancer detection and monitoring methods. Circulating tumor DNA (ctDNA) is DNA that has escaped from tumor cells and is free-floating in the bloodstream, meaning that genetic information about the developing tumor can be obtained without the need to invasively extract tumor tissue. cBioPortal wants to display the insights obtained from these “liquid biopsies” onto their existing Patient View page. I propose to create a global view of ctDNA information by modifying their existing Genomic Overview to display allele frequencies, allowing users to identify at a glance mutated genes of interest. Mutated genes can be tracked by clicking on the gene, which would display a plot of the gene’s mutation concentration over time. A heatmap of selected genes can also be generated to monitor tumor heterogeneity over time. Another feature could consist of plots to track whether a mutated gene produces a differential time to relapse or survival time compared to the unaltered gene. By visualizing ctDNA results on the cBioPortal interface, I can participate in adding an exciting new clinician tool for personalized cancer genomics.</p>

Develop distributed edge caching strategies using Web Standard Cache API for sub-50ms storefront responses.

<p>The proposed project deals with the development of two Drupal modules, for storage and visualizations of Complex Biological Graph. Both the proposed modules will be able to integrate along with Tripal and can be used by the Scientific community for the construction of genetic website, publish genomic data. The primary aim of the project is to optimize querying by using a Graph Database and also generate a good User Interface.</p>

The cBioPortal organization is dedicated to assisting clinicians and researchers in the analysis of complex cancer genomics data. And cBioPortal includes OncoKB annotation in it's view to provide detailed biological effect and clinical implications for each variant. Despite the availability of a standard API for annotating alterations, users without a computational background still find it challenging to annotate their variants. This project addresses this gap by first developing a pipeline to fetch a list of genomic variants from the MSK-IMPACT clinical cohort that have not been curated by OncoKB. The approach utilizes distributed parallel computing to accelerate the identification of target variants while ensuring data consistency through regular monitoring and timely updates. Then, a web interface has been designed to allow users to view and annotate these uncurated variants directly from the webpage. This interface supports searching and sorting functionalities, enabling users to find specific variants and prioritize them for OncoKB curation. The outcome of this initiative includes an automated pipeline, powered by AirFlow, for the continuous retrieval and verification of uncurated variants, alongside a user-friendly interface that facilitates the direct annotation of variants by users through webpage interactions. This project aims to simplify the variant annotation process, making it more accessible to a broader audience and further advancing the field of precision oncology.

<p>Kibana Visualize app needs a new calendar visualization similar to <a href="https://www.elastic.co/blog/awesome-new-kibana-visualizations-heatmap-and-point-series" target="_blank">Kibana heatmap</a>, which provides single-day or multi-day events markings in varying colors based on different metrics. It should also play well with the visualization editor, filtering, and Dashboard.</p>

The Music Listening History Dataset is pretty damn impressive; It contains ~27 billion logs of real-world data from last.fm scrobbles distributed into 18 chunks summing up to ~611.39 GB of compressed text files. This results in 583k users, 555k unique artists, 900k albums, and 7M tracks. Here each scrobble is represented in the following format: timestamp, artist-MBID, release-MBID, recording-MBID. (Source: https://simssa.ca/assets/files/gabriel-MLHD-ismir2017.pdf) Unfortunately, this data has some significant fallbacks due to last.fm’s out-of-date matching algorithms with the MusicBrainz DB, resulting in frequent mismatches & errors in the recording-MBID data, affecting the quality of the available dataset. Overall, the goal of this project is to create an updated version of the MLHD in the same format as the original, but with incorrect data resolved and invalid data removed.

<p>The project aims to add more options to fabric maven plugin for building images for OpenShift build mode. Right now fmp supports two kinds of binary builds namely s2i and docker for OpenShift build mode. The project aims at extending the support for other options such as Buildah and GoogleContainerTools/jib. The projects aims at solving certain aspects such as:-</p> <ol> <li>Separation Of Concerns</li> <li>Daemonless/Security</li> <li>Reproducibility</li> <li>Minimal Images</li> <li>Performance</li> <li>Dockerfile-less</li> <li>Simplifying the build flow</li> </ol> <p>Also there will be unit test cases added for each added feature.</p>

Sugar Activity on Demand addresses a key barrier in Sugar Labs: the difficulty learners face in creating their own activities due to the need for programming knowledge. This limits access to constructionist learning, where students learn best by building meaningful projects. This project introduces an AI-assisted system that allows learners to describe an activity in natural language and receive a fully functional, installable Sugar activity. The system combines a model-agnostic LLM pipeline, a retrieval-augmented knowledge base built from real Sugar Activity source code, and an AST-based validator to ensure that generated Python code is both correct and safe. Activities are generated with proper GTK3 interfaces, toolbar integration, and Journal support, ensuring they are fully compatible with the Sugar ecosystem. Beyond generation, the project emphasizes learning through a Reflective Studio, where learners explore, understand, and modify the generated code. Using scaffolded challenges, inline annotations, and reflection prompts, the system follows the constructionist Use → Modify → Create progression, enabling learners to gradually take ownership of their creations rather than passively consuming generated output. Deliverables AI-powered activity generation pipeline (prompt → plan → code → installable bundle) RAG-based knowledge system using real Sugar Activity examples AST-based security validation and safe code generation framework Interactive Reflective Studio with guided editing, annotations, and challenges Integration into Sugar’s Home View with a seamless “Create with AI” entry point Support for iterative refinement, version history, and sharing via the Sugar Journal This project aligns with Sugar Labs’ constructionist philosophy by transforming AI from a passive generator into an active learning partner, empowering learners not just to use software, but to understand and create it.

<p>Give homeserver admins the ability to restrict who can register an account by requiring users to submit a token during registration. See <a href="https://calcuode.com/matrix-gsoc/" target="_blank">https://calcuode.com/matrix-gsoc/</a> for more details.</p>

Accord Project Playground: Empowering Developers Through Interactive Learning Problem: The Accord Project offers powerful functionalities for smart legal contracts, but grasping these concepts can be challenging for developers with varying backgrounds. Existing documentation and resources may not provide an engaging and interactive learning experience. Solution: Proposing and developing a user-friendly Accord Project Playground. This web-based platform will provide an interactive environment for developers to experiment with Accord Project features through: Modern UI/UX Design: An intuitive and visually appealing interface that aligns with the Accord Project's branding. Interactive Code Samples: Live code editing and preview capabilities to demonstrate functionalities in a hands-on manner. Integrated Learning Resources: Comprehensive documentation, tutorials, and search functionality for efficient learning. Sample Management: Functionality to save and export user-created Accord Project code (specific format to be determined). Integration of Live Chat-Bot. Open-Source Principles: Adherence to open-source best practices for transparency, collaboration, and maintainability. Deliverables: * A fully functional Accord Project Playground website with interactive learning features. * Comprehensive documentation for the playground itself, including installation, setup, and usage guides. * A well-structured codebase with clear version control and adherence to coding standards. * A thriving contributor's community with a contributor's guide outlining participation procedures. Impact: By creating this Accord Project Playground, I aim to: * Lower the barrier to entry for developers interested in Accord Project technology. * Foster a more engaged and active Accord Project developer community. * Enhance the overall accessibility and user experience of the Accord Project.

<p>The 21st century ushered with it the age of smart and predictive technology with the optimum use of resources to make life easier. In accordance with this trend, the proposal is to leverage machine learning algorithms for improved traffic avoidance, determine the energy consumption of the electric vehicles, simulation of driving, visualisation of the route taken by a car, route prediction and providing a smart notification system. The Fuel_prediction module has functionalities including predicting the energy consumption, the amount of CO2 that is saved from being emitted to the environment and the recharge time required for the journey. The Route_option module focuses on leveraging human knowledge to get the best route for traffic avoidance. The Trajectory module shows the visualization of the route a car takes. The Route_predictor helps to predict the route that the car will take based on the previous history. The Driving_simulator module is a simulator for vehicles to learn how to drive themselves. The Smart_notifcation module helps in filtering the notifications in order to avoid spamming the user.</p>

While Sugar has lots of activities, you can never have enough math games and puzzles. This project will include developing 8 new math activities for Sugar inspired by the ideas provided here (https://www.cut-the-knot.org) by Alexander Bogomolny

<h3>Goal</h3> <p>This project aims at fully implementing end-to-end encryption in matrix-python-sdk, following the official implementation guide and making use of the Python bindings already present in libolm.</p> <h4>Rationale</h4> <p>Currently, even though end-to-end encryption has landed in Matrix for over a year, only the three SDK upon which is built Riot on different platforms (JS, Android and iOS) ship with encryption. On desktop, this situation prevents writing clients, bots and bridges that can interact with encrypted rooms in any other language than javascript. Tackling this issue would benefit the matrix ecosystem by seeing more featureful projects emerge in a variety of languages (Python in this case). It also supports the Matrix long-term goal of having E2E encryption turned on by default in private rooms.</p>