metadata: {"signature": "0x78b6c4eb1ebd2c0912c4ffb0e16638f2b73b87ea8d59622d28f266d0b17893e51d58c4713531bd4b041c9354338107aed63106b883f26a882ecefba995d747131c", "application": {"round": "0xc34745b3852df32d5958be88df2bee0a83474001", "answers": [{"type": "email", "hidden": true, "question": "Email Address", "questionId": 0, "encryptedAnswer": {"ciphertext": "jrKISQ0B4gTf1m+1Au6+I6spkSX1BYoakIDbx6SF8eDwh26seeLh/TfhW+ZCFdbU", "encryptedSymmetricKey": "8848ec0316d14128fe2f4ac8c93611138f1cedefb588373e4c987a10aae84bd3dd4cfc7804ac583bc3d58cc3292ffb12b8dc014b8a01805754ebe319133118ac47a072675d8df3fd5b30b9f21bd701f5de6672ea1e78000a484929cc8c44e6a14aef46ff691ba54e1ef4123a6f2ca33eebc62b0458ec6ad4f0f8c59779b7a2bc00000000000000200bf509df00cf40ddb2ba70d40867c64734f759deb37a642009dc54f9864b46059d04f3f88db278f860418ccd9239af87"}}, {"type": "short-answer", "answer": "Self-funded", "hidden": false, "question": "Funding Sources", "questionId": 1}, {"type": "number", "answer": "1", "hidden": false, "question": "Team Size", "questionId": 2}], "project": {"id": "424:0xDF9BF58Aa1A1B73F0e214d79C652a7dd37a6074e:438", "title": "Moyo", "logoImg": "bafkreigaq2emdtx26bdbhprkrtbqi62i7rynbq42l2cazkawiuqkklwa5i", "metaPtr": {"pointer": "bafkreicmshmypxlkaumzbddl6ksqvvtaqsglfpfvjpml7nkaepkaxrl3ii", "protocol": "1"}, "website": "https://moyo-ldcrc.softr.app/", "createdAt": 1700520559341, "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..5onekz9vq3yCHvCmjxiqgfdMxkY7XpAiUdQKzUfV1-PEOG2E2AvoF4eeiWEJ0TBo56BM9p2D2m7WW4ZaHr27Bw", "type": "Ed25519Signature2018", "created": "2023-11-20T22:49:00.854Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-11-20T22:49:00.853Z", "expirationDate": "2024-02-18T22:49:00.853Z", "credentialSubject": {"id": "did:pkh:eip155:1:0xc7978F8Cb4d826E209911237676d1eeAF17942F4", "hash": "v0.0.0:rgo62RtcxrrdxF4XJ6/9JXkBxGwdb174EbwXgfUIhRM=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#ledgerback"}}}, "description": "### What is Moyo?\nMoyo is a digital catalogue and knowledge graph curating, mining, and expanding access to learning content from the forefront of innovation, technology, governance, and science (\"the frontier\").\n\n### Problem\n**Fragmented Information Landscape** \n\nLearning content on frontier-related topics is fragmented. Learning content is published and stored on many different platforms and various multimedia formats, which inhibits 1) learners from enhancing their expertise via new content and finding reviews of existing content to determine the quality of the educational content, 2) educators from finding new learners for their content and reviews of existing content, and 3) learning designers from knowing which educational content to develop and learning from user feedback on educational content\n\n\n### Solution\n**Unified Digital Catalogue and Knowledge Graph Representation**\n\nOrganize learning content from many diverse, online educational sources into a unified digital catalogue, and represent it as a knowledge graph to show connections between learning content, content creators, teachers, schools, concepts, and to develop learning roadmaps. \n\nThe digital catalogue and knowledge graph will be accessible to educators, learning designers, and learners through searchable web-interfaces, APIs, newsletters, and data visualizations.\n\n### Work-to-Date\nOur current outputs include: \n\n1) Moyo Explorer: a searchable web-interface demo for the digital catalogue, with directories for schools and learning content, available at: https://moyo-ldcrc.softr.app/\n\n*Note: Our current outputs are a work-in-progress.*\n\n### Use-cases\nPossible use-cases with the digital catalogue and knowledge graph include: \n\n1) analysis and visualization of Moyo data, \n2) create collections from the digital catalogue, and \n3) recommend learning content based on various filters, \n4) fill metadata gaps, \n5) create and apply metrics on content from the digital catalogue, \n7) monitor content-related events (e.g., Twitter mentions), \n8) developing learning maps to guide anyone from being a novice to an expert on frontier-related topics\n\n### Target Audience\nThis project primarily benefits four groups: \n\n1) students and the public: Find learning content and learning maps on topics from the frontier; \n3) businesses: enables businesses to create new tools and innovate using the digital catalogue and knowledge graph as a resource; and\n4) educators and learning designers: Increase the visibility of educators and learning designers by driving traffic to their websites, promoting their learning content in our newsletters, and curating user feedback on their learning content.\n\n### Goals\n\nThrough Moyo, we hope to: \n\n1) make frontier-related learning content discoverable, accessible, and connected; \n2) enhance expertise on frontier-related knowledge and skills; and\n3) encourage the development of open frontier-related learning content.", "lastUpdated": 0, "projectGithub": "Ledgerback", "projectTwitter": "ledgerback"}, "recipient": "0xc7978F8Cb4d826E209911237676d1eeAF17942F4"}}