Open Software & Datasets

Description: Using various data sources from the RBHU Budapest Campus Building BP201, BP205, (BP106), we created this data repository containing the following types of data:

Time-Series Data from Sensors: This includes temperature, humidity, air quality, pressure, flow, energy consumption, valve and damper positions, pump and fan status, control system outputs, switches and relays status, enthalpy, operation counters, setpoints, control values, alarm, and fault indicators.

Type of Publication: dataset

Description: Using various data sources from the RBHU Budapest Campus Building BP201, BP205, (BP106), we created this data repository containing the following types of data:

Time-Series Data from Sensors: This includes temperature, humidity, air quality, pressure, flow, energy consumption, valve and damper positions, pump and fan status, control system outputs, switches and relays status, enthalpy, operation counters, setpoints, control values, alarm, and fault indicators.

Type of Publication: dataset

Publisher: RBHU

Description: Domain adaptation toolbox compatible with scikit-learn and pytorch

Type of Publication: software

Description: FactCheckBureau: An end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines.

Fact-checkers are overwhelmed by the volume of claims they need to pay attention to fight misinformation. Even once debunked, a claim may still be spread by people unaware that it is false, or it may be recycled as a source of inspiration by malicious users. Hence, the importance of fact-check (FC) retrieval as a research problem: given a claim and a database of previous checks, find the checks relevant to the claim. Existing solutions addressing this problem rely on the strategy of retrieve and re-rank relevant documents. We have built FactCheckBureau, an end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines. We also present a corpus 1 we have built, which can be used in further research to test fact-check retrieval tools.

Paper: https://zenodo.org/records/13868429

Repository: https://gitlab.inria.fr/cedar/factcheckbureau

Type of Publication: Dataset

Title of Conference: 33rd ACM International Conference on Information and Knowledge Management (CIKM) , Boise, Idaho, US, 21-25 October

Description: This repository contains the data collected during and the code used to analyze the Beauty Survey. A pre-print of the associated paper including our analysis and findings can be found at this link.

Zip files have been uploaded to this repository to stay within the file limit enforced by Zenodo. To use our code and data simply unzip these folders while mainting the current directory structure. 

While the code here is complete and stands on its own, any new features added can be found in the GitHub repository associated with this project (link).

AG and NO are supported by a nominal grant received at the ELLIS Unit Alicante Foundation from the Regional Government of Valencia in Spain (Convenio Singular signed with Generalitat Valenciana, Conselleria de Innovacion, Industria, Comercio y Turismo, Direccion General de Innovacion), along with grants from the European Union’s Horizon 2020 research and innovation programme – ELISE (grant agreement 951847) and ELIAS (grant agreement  101120237), and by grants from the Banc Sabadell Foundation and Intel corporation. BL is partially supported by the European Union’s Horizon Europe research and innovation program under grant agreement No. 101120237 (ELIAS) and by the PNRR project FAIR – Future AI Research (PE00000013), under the NRRP MUR program funded by the NextGenerationEU.

Type of Publication: Dataset