https://doi.org/10.1140/epjds/s13688-017-0104-x
Commentary
Topological analysis of data
1
ISI Foundation, via Alassio 11c, Turin, Italy
2
Dipartimento di Scienze Matematiche “G.L. Lagrange”, Politecnico di Torino, corso Duca degli Abruzzi 24, Turin, Italy
* e-mail: alice.patania@isi.it
Received:
15
May
2017
Accepted:
29
May
2017
Published online:
6
June
2017
Propelled by a fast evolving landscape of techniques and datasets, data science is growing rapidly. Against this background, topological data analysis (TDA) has carved itself a niche for the analysis of datasets that present complex interactions and rich structures. Its distinctive feature, topology, allows TDA to detect, quantify and compare the mesoscopic structures of data, while also providing a language able to encode interactions beyond networks. Here we briefly present the TDA paradigm and some applications, in order to highlight its relevance to the data science community.
Key words: topological data analysis / simplicial complexes / persistent homology
© The Author(s), 2017
