TY - GEN
T1 - Analyzing the evolution of linked vocabularies
AU - Abdel-Qader, Mohammad
AU - Vagliano, Iacopo
AU - Scherp, Ansgar
N1 - Funding Information: Acknowledgment. This work was supported by the DFG (German Research Foundation) with the LOC-DB project (Grants No. GZ:SCHE 1687/5-1) and the EU’s Horizon 2020 programme under grant agreement H2020-693092 MOVING. Publisher Copyright: © Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Reusing terms results in a Network of Linked vOcabularies (NeLO), where the nodes are the vocabularies that use at least one term from some other vocabulary and thus depend on each other. These dependencies become a problem when vocabularies in the network change, e. g., when terms are deprecated or deleted. In these cases, all dependent vocabularies in the network need to be updated. So far, there has been no study that analyzes vocabulary changes in NeLO over time. To address this shortcoming, we compute the state of NeLO from the available versions of the vocabularies over 17 years. We analyze static parameters of NeLO such as its size, density, average degree, and the most important vocabularies at certain points in time. We further investigate how NeLO changes over time. Specifically, we measure the impact of a change in one vocabulary to others, how the reuse of terms changes, and the importance of vocabularies changes. Our analyses provide for the first time in-depth insights into the structure and evolution of NeLO. This study helps ontology engineers to identify shortcomings of the data modeling and to assess the dependencies implied with reusing a specific vocabulary.
AB - Reusing terms results in a Network of Linked vOcabularies (NeLO), where the nodes are the vocabularies that use at least one term from some other vocabulary and thus depend on each other. These dependencies become a problem when vocabularies in the network change, e. g., when terms are deprecated or deleted. In these cases, all dependent vocabularies in the network need to be updated. So far, there has been no study that analyzes vocabulary changes in NeLO over time. To address this shortcoming, we compute the state of NeLO from the available versions of the vocabularies over 17 years. We analyze static parameters of NeLO such as its size, density, average degree, and the most important vocabularies at certain points in time. We further investigate how NeLO changes over time. Specifically, we measure the impact of a change in one vocabulary to others, how the reuse of terms changes, and the importance of vocabularies changes. Our analyses provide for the first time in-depth insights into the structure and evolution of NeLO. This study helps ontology engineers to identify shortcomings of the data modeling and to assess the dependencies implied with reusing a specific vocabulary.
UR - http://www.scopus.com/inward/record.url?scp=85065482533&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-030-19274-7_29
DO - https://doi.org/10.1007/978-3-030-19274-7_29
M3 - Conference contribution
SN - 9783030192730
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 409
EP - 424
BT - Web Engineering - 19th International Conference, ICWE 2019, Proceedings
A2 - Frasincar, Flavius
A2 - Bakaev, Maxim
A2 - Ko, In-Young
PB - Springer - Verlag
T2 - 19th International Conference on Web Engineering, ICWE 2019
Y2 - 11 June 2019 through 14 June 2019
ER -