Web Application Development

project proposals

A project proposal could be chosen by maximum 3 teams. A team includes 2—3 persons.

In order to be taken into consideration for evaluation, each team should fill in the WADe Project Assessment form (deadline: Monday, 21 October) – submitted project applications.

  1. BiR (Big Data Retriever)

    There are plenty of interesting resources provided by Wikidata via its SPARQL endpoint. Develop a (micro-)service-based platform able to "intelligently" query, compare, visualize, share, summarize, etc. large (sets of) data/knowledge and additional resources. Also, this Web system will recommend related information and/or similar resources available in other languages. Various computations could be performed by using existing big data techniques and tools. Bonus: the use of natural user interactions.

  2. ComIT (Competitive IT Events)

    Implement a service-oriented platform able to explore, filter, visualize, and update the information regarding the participants to various IT competitive events (e.g., programming or algorithm-related competitions, Web challenges, hackathons, etc.) and their submitted solutions. The system will provide useful recommendations about alternative solutions, additional tips & tricks, similar problems and events, tutorials, on-line courses, public code repositories, interesting persons (mentors, winners, organizing entities, sponsors, and others). In conjunction to DBpedia and/or Wikidata, the access to desired data and functionalities will be given via a SPARQL endpoint in various formats – at least HTML+RDFa and JSON-LD having embedded software source code schema.org constructs. See also, Stack Exchange Data Explorer.

  3. CryS (Cryptocurrency Smart Manager)

    Starting with Description Of A CryptoCurrency, develop a modular Web system capable to express and manage the knowledge about existing cryptocurrencies and their (meta-)data. Each functionality will be implemented by a (micro-)service and all queries will be performed via a SPARQL endpoint. Exposed information will be available in multiple formats (at least, HTML+RDFa and JSON-LD). Also, multiple visualizations will be provided. For additional resources, explore CryptoMinded.

  4. DaBS (DataBase Smart Web Tool)

    By using the DB Ontology and other knowledge models, create a Web tool able to compare, run, visualize, and recommend various database management systems (DBMS) according to developer preferences and specific usages – e.g., implementing financial desktop applications, e-commerce Web applications, educational platforms, document management systems, etc. The tool will support various paradigms (relational, graph-based, key-value, tree-like,...), query languages (SQL, GQL, SPARQL, GraphQL, XQuery), platforms (servers) + running environments (desktop, Web, cloud), specific contexts – i.e. focusing on optimizing queries, redundancy, security, performance, schema versus schema-less approaches, programming languages/paradigms, and others. Resources: Awesome Database and DB Weekly.

  5. Gezr (Gesture Analyzer)

    Having a number of Webcam-captured video streams, build a Web application that detect, classify, compare, and synchronize hand and arm gestures performed by (human) users. A conceptual model will be created/(re)used in order to express (classes of) gestures, anatomic features, associated actions, etc. A rule-based approach could be adopted – for example, if the "wave" gesture is detected in at least 74% of video feeds exposed by a video-conferencing system, then the conference session will be ended. Also, different statistics of interest will be offered in graphical form and as JSON-LD data. Study An Ontology for Reasoning on Body-based Gestures. Consult also Awesome Streaming and Recognition APIs. Bonus: capturing and exposing useful provenance.

  6. Imor (Image Smart Processor)

    Considering the Kaggle Image Datasets, develop an extensible microservice-based system able to perform processing tasks such as browsing, smart faceted searching & filtering, etc. Adopting both deep learning (or machine learning) techniques and semantic Web technologies, the platform will be able to generate various visualizations (e.g., semantic zoom), correlations, classifications, and recommendations exposed via a SPARQL endpoint. Also, a comparison study will be provided to explain the obtained results.

  7. MePr (On-line Media Provenance)

    Based on on-line media services, create a system (such as Web platform, framework, component) able to model and manage – including operations like query, visualize, recommend,... – the knowledge about the provenance of each newspaper resource, which content could be textual or multimedia (pictures, illustrations, presentations, podcasts – audio files available for streaming, videos,...), possibly available in different languages and structured by using meta-data/classification models like DCMI, ITPC or Social Semantic Web Thesaurus. A SPARQL endpoint – exposing RDFa and JSON-LD including schema.org-based markups for news – is also necessary to provide access data of interest (e.g., list fresh editorials concerning a specific topic, provide the articles under 4000 words written in English or French about the international IT contests, offer the title + description of the articles/documentaries posted on-line by the Romanian journalists). As inspiration, study The New York Times APIs, The London Gazette, and Bibliothèque nationale de France.

  8. MuG (Museum Web Guide)

    Build a smart responsive Web application that guides a museum visitor. The application could be downloaded via a public/private app store by using the QR code printed on the museum ticket – consult also a list of QR APIs. The application will take advantage of the position of the user in the museum – using sensor networks, NFC, RFID, Web beacons, etc. – to determine where (s)he is and provide her/him useful audio and visual information based on existing data about Romanian museums, plus Wikidata. If a visitor wants to find out more, (s)he would walk to certain exhibits in order to have access to details of interest (for example, each exhibit could provide its specific QR code pointing out to useful knowledge). At the end of the tour, the application will offer an overview and the photo/video album – in general, a creative work – (s)he took along the way presented as time line. This work – plus the user comments/reviews regarding the tour – could be also shared on several significant social networks and accessed via a SPARQL endpoint. Bonus: the use of natural user interactions – for example, a conversational user interface provided by various UI bots.

  9. NotIS (Notarial Info Smart Tool)

    Using the official data regarding public notary entities and authorized translators + interpreters, develop a smart modular Web system capable to provide support for locating offices and services – such as notarized documents: acknowledgments, oaths/affirmations, copy certification, signature witnessing, others legal procedures – according to user preferences, geographical places, fees, restrictions, and other aspects (e.g., support for foreign citizens) – consider also legal paper provenance. Via SPARQL endpoints, the application will offer useful maps – see also Place schema.org concept – and additional knowledge (contact info, timetable, reviews, related points of interest) about each notary office. Bonus: adopting Solid principles & tools.

  10. ODaVi (EU Open Datasets Visualizer)

    Considering the datasets provided by the EU Open Data Portal, build a modular Web tool able to provide useful visualizations for better understanding of data/information/knowledge. The core functionalities will be accessed via a SPARQL endpoint. Different extensions (at least 3) will be provided in order to demonstrate specific operations – e.g., "intelligent" filtering, layered visualizations, trend computations, etc. Bonus: exposing 3D visualizations by using WebGL and/or WebVR.

  11. SATo (WebDev Smart Aid Tool)

    Develop a multi-device (micro-)service-oriented system able to model and manage, in a smart way, public technical content regarding Web development (such as tutorials, presentations, examples of source-code, news, etc.) from multiple sources such as DevDocs, GitHub Pages, MDN Web Docs, Programmable Web, Reddit, and others. Using the Linked Data principles, the application will generate and expose for human users and software – via a SPARQL endpoint – knowledge of interest for Web developers according to various criteria: topic (e.g., a certain programming language/paradigm, only guides/references about a specific framework), target platform, purpose, geographical area, period of time, user preferences,... Additional knowledge provided by Wikidata and ACM Computing Classification System will be used.

  12. ViPS (Video Processing Smart Platform)

    By using the YouTube-8M labeled video dataset, create an extensible microservice-based platform able to perform processing tasks such as browsing, smart faceted searching & filtering, etc. Adopting both machine learning (or deep learning) techniques and semantic Web technologies, the system will be able to make various visualizations (e.g., semantic zoom), correlations, classifications, and recommendations exposed via a SPARQL endpoint. Also, a comparison study will be provided to explain the obtained results.

  13. ViRTo (Vinyl Recommender Tool)

    Build a semantic Web application able to "intelligently" recommend – by exposing a SPARQL endpoint – vinyl music records according to various criteria: user preferences (specified via controlled natural language constructs such as "I always like/love/prefer classical music, especially opera music by Rossini or Verdi and performed by Angela Gheorghiu or Juan Diego Flórez; I sometimes like progressive rock and post-rock; I like only metal albums released before 2000; I always dislike/hate rap and hip-hop; I dislike songs produced by Flood in the last 25 years"), past song purchases on various music stores, playlists – available online via music streaming services Spotify and alternatives – and/or locally (i.e. uploading a JSPF/XSPF document). The playlists could be created by the user or shared by her/his virtual "friends" (consider at least one social network). The system will use several music-related knowledge models (e.g., Music Ontology or MusicRecording concept from schema.org) and available public resources: Free Music Archive, MusicBrainz, Musicmoz Music Styles. Bonus: using Solid principles & tools. Inspiration: Musicmap.

  14. Watr (Web Data Commons Analyzer)

    Create a Web tool able to perform various processing tasks regarding the meta-data available in RDFa and HTML5 microdata formats provided by the Web Data Commons. Using a modular approach, a minimal set of operations will be implemented: visualize, classify, compare, and match/align. The queries will be performed via a SPARQL endpoint, the obtained results being available in HTML and JSON(-LD) formats. Various statistics, modeled with the RDF Data Cube vocabulary, will be also exposed.

  15. WeSoR (Web Social Recommender)

    Develop a Web modular application able to recommend certain items of interest (people, events, places, other things) according to a given FOAF graph built for a specific user – based on her/his social media profile(s) – by considering multiple similar features/properties. For example, suggesting the members of an IT team based on desired skills (excellent knowledge of certain areas like Web technologies + software engineering + open hardware), geographic location (i.e. from Romania and China only), technical preferences (e.g., using free software), background info (demographics, education, occupation history, driving license, other competencies), hobbies (i.e. horror movies + classical music), aversions (e.g., communication by phone, sport, politics) and so on. The system should be smart enough to improve recommendations based on various methods such as user feedback, reasoning, and/or machine learning. The recommended items will be available via a SPARQL endpoint.

  16. WTra (Web Traffic Signs)

    Having (snapshots of) video recordings – captured via a Webcam or uploaded by a user – regarding an urban route (frequently/randomly) used by a person or a group of persons (e.g., by using a bike/car/bus), develop a (micro-)service-based Web system able to detect road/traffic signs. This detection process could be performed automatically by using specific public APIs and/or by using user-reported info (optionally, via external navigation services like Waze or alternatives). A specific ontology specified in OWL will be created. For each recognized (category of) road sign, a SPARQL end-point will offer various knowledge: meaning, type, legal regulations, relationships to other traffic signs, practical advices, context of use, comparisons, plus suggestions regarding user (driver/pedestrian) behavior. Consult the Romanian Traffic Code and Comparison of European road signs. Additional resources: Traffic Sign Detection Articles @ Google Scholar + Traffic Sign Recognition Code Repositories @ GitHub.