|
7 | 7 | "project_description": "Collaborative analytics for the Energy Sector based on innovative collaborative forecasting algorithms that improve renewable energy or load predictability by combining data from different data owners.", |
8 | 8 | "project_topic": "predico", |
9 | 9 | "project_tags": [ |
| 10 | + "collaborative-forecasting", |
10 | 11 | "collaborative-analytics", |
11 | 12 | "predico", |
12 | | - "data-market", |
13 | | - "collaborative-forecasting" |
| 13 | + "data-market" |
14 | 14 | ], |
15 | 15 | "top_repositories": [ |
16 | 16 | { |
|
37 | 37 | "project_description": "Enershare defines a Data-Driven Reference Architecture for the energy domain, which is compliant with FIWARE, IDSA and GAIA-X. It creates a marketplace based on Blockchain and Smart Contracts with the aim of improving mutual trust amongst the actors of the ecosystem and increasing the security of the shared data.", |
38 | 38 | "project_topic": "enershare", |
39 | 39 | "project_tags": [ |
40 | | - "python", |
41 | | - "energy-communities", |
42 | | - "client-library", |
43 | | - "tno-security-gateway", |
44 | | - "renewable-energy-communities", |
45 | 40 | "enershare", |
| 41 | + "price-optimization", |
| 42 | + "tno-security-gateway", |
46 | 43 | "dataspaces", |
47 | 44 | "energy", |
48 | | - "price-optimization" |
| 45 | + "renewable-energy-communities", |
| 46 | + "python", |
| 47 | + "energy-communities", |
| 48 | + "client-library" |
49 | 49 | ], |
50 | 50 | "top_repositories": [ |
51 | 51 | { |
|
100 | 100 | "project_description": "GREEN.DAT.AI aims to channel the potential of AI towards the goals of the European Green Deal, by developing novel Energy-Efficient Large-Scale Data Analytics Services, ready-to-use in industrial AI-based systems, while reducing the environmental impact of data management processes.", |
101 | 101 | "project_topic": "greendatai", |
102 | 102 | "project_tags": [ |
103 | | - "python", |
104 | | - "client-library", |
105 | | - "greendatai", |
| 103 | + "enershare", |
| 104 | + "collaborative-forecasting", |
| 105 | + "energy", |
| 106 | + "data-marketplace", |
106 | 107 | "machine-learning-algorithms", |
107 | | - "data-sharing", |
| 108 | + "greendatai", |
| 109 | + "client-library", |
| 110 | + "python", |
108 | 111 | "data-sharing-incentives", |
109 | | - "data-marketplace", |
110 | | - "collaborative-forecasting", |
111 | | - "enershare", |
112 | | - "energy" |
| 112 | + "data-sharing" |
113 | 113 | ], |
114 | 114 | "top_repositories": [ |
115 | 115 | { |
|
128 | 128 | ] |
129 | 129 | }, |
130 | 130 | { |
131 | | - "name": "data-sharing-barter-incentives-forecast", |
132 | | - "url": "https://github.com/INESCTEC/data-sharing-barter-incentives-forecast", |
| 131 | + "name": "data-sharing-barter-incentives-client", |
| 132 | + "url": "https://github.com/INESCTEC/data-sharing-barter-incentives-client", |
133 | 133 | "stars": 2, |
134 | 134 | "is_fork": false, |
135 | 135 | "topics": [ |
136 | | - "collaborative-forecasting", |
137 | | - "data-sharing-incentives", |
| 136 | + "client-library", |
| 137 | + "python", |
138 | 138 | "enershare", |
139 | | - "machine-learning-algorithms", |
140 | 139 | "greendatai", |
141 | 140 | "data-marketplace", |
142 | 141 | "energy" |
143 | 142 | ] |
144 | 143 | }, |
145 | 144 | { |
146 | | - "name": "data-sharing-barter-incentives-client", |
147 | | - "url": "https://github.com/INESCTEC/data-sharing-barter-incentives-client", |
| 145 | + "name": "data-sharing-barter-incentives-forecast", |
| 146 | + "url": "https://github.com/INESCTEC/data-sharing-barter-incentives-forecast", |
148 | 147 | "stars": 2, |
149 | 148 | "is_fork": false, |
150 | 149 | "topics": [ |
151 | | - "client-library", |
152 | | - "python", |
| 150 | + "collaborative-forecasting", |
| 151 | + "data-sharing-incentives", |
153 | 152 | "enershare", |
| 153 | + "machine-learning-algorithms", |
154 | 154 | "greendatai", |
155 | 155 | "data-marketplace", |
156 | 156 | "energy" |
|
168 | 168 | "project_description": "InterConnect gathers 50 European entities to develop and demonstrate advanced solutions for connecting and converging digital homes and buildings with the electricity sector.", |
169 | 169 | "project_topic": "interconnect", |
170 | 170 | "project_tags": [ |
171 | | - "python", |
172 | 171 | "interconnect", |
| 172 | + "energy", |
173 | 173 | "electric-vehicles", |
174 | | - "incentives", |
175 | | - "recommender", |
176 | 174 | "causality", |
177 | | - "energy" |
| 175 | + "recommender", |
| 176 | + "python", |
| 177 | + "incentives" |
178 | 178 | ], |
179 | 179 | "top_repositories": [ |
180 | 180 | { |
|
317 | 317 | "project_description": "EMB3Rs stands for \u201cUser-driven Energy-Matching & Business Prospection Tool for Industrial Excess Heat/Cold Reduction, Recovery and Redistribution.", |
318 | 318 | "project_topic": "emb3rs", |
319 | 319 | "project_tags": [ |
320 | | - "emb3rs", |
321 | | - "energy" |
| 320 | + "energy", |
| 321 | + "emb3rs" |
322 | 322 | ], |
323 | 323 | "top_repositories": [ |
324 | 324 | { |
|
343 | 343 | "project_description": "Robotised solutions and intelligent systems for agriculture and forestry.", |
344 | 344 | "project_topic": "tribe", |
345 | 345 | "project_tags": [ |
346 | | - "robotics", |
347 | | - "tribe", |
348 | 346 | "slam", |
349 | | - "agro-food" |
| 347 | + "agro-food", |
| 348 | + "tribe", |
| 349 | + "robotics" |
350 | 350 | ], |
351 | 351 | "top_repositories": [ |
352 | 352 | { |
|
393 | 393 | "project_description": "To disclose the state-of-the-art in advanced production technologies through the demonstration of research, experimentation and advanced training results. iiLab supports technology-based innovation in public and private organisations, thus contributing to the development of their skills in the development, adoption and implementation of advanced production technologies, leading to a sustainable competitiveness in the circular economy context.", |
394 | 394 | "project_topic": "iilab", |
395 | 395 | "project_tags": [ |
396 | | - "robotics", |
397 | | - "iilab" |
| 396 | + "iilab", |
| 397 | + "robotics" |
398 | 398 | ], |
399 | 399 | "top_repositories": [ |
400 | 400 | { |
|
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