%0 Conference Paper %1 hanika2024repository %A Hanika, Tom %A Jäschke, Robert %B Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures %D 2024 %K 2024 contexts itegpub kde kdepub myown publist repository %T A Repository for Formal Contexts %U https://arxiv.org/abs/2404.04344 %X Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.

@inproceedings{hanika2024repository, abstract = {Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this. }, added-at = {2024-08-22T10:16:40.000+0200}, archiveprefix = {arXiv}, author = {Hanika, Tom and Jäschke, Robert}, biburl = {https://www.bibsonomy.org/bibtex/29cd9667ebadfba3a36f95fd901e32724/tomhanika}, booktitle = {Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures}, eprint = {2404.04344}, interhash = {a0e0a088deeffb98b9fc52780d8caa11}, intrahash = {9cd9667ebadfba3a36f95fd901e32724}, keywords = {2024 contexts itegpub kde kdepub myown publist repository}, primaryclass = {id='cs.AI' full_name='Artificial Intelligence' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.'}, timestamp = {2025-01-06T11:48:26.000+0100}, title = {A Repository for Formal Contexts}, url = {https://arxiv.org/abs/2404.04344}, year = 2024 }