TY - GEN
T1 - Collaborative Management of Traffic Accidents Data for Social Impact Analytics
AU - Osório, A. Luís
AU - Antunes, Cláudia
AU - Camarinha-Matos, Luís M.
AU - Gonçalves, Carlos
N1 - Funding Information:
Acknowledgments. This work is supported in part by the ANSR/SINCRO project (GIATSI/ISEL/IPL research group) and by the Portuguese FCT programs UIDB/00066/2020 (Center of Technology and Systems – CTS) and VisBig (PTDC/CCI-CIF/28939/2017).
Publisher Copyright:
© 2022, IFIP International Federation for Information Processing.
PY - 2022/9
Y1 - 2022/9
N2 - Traffic accidents have a devastating effect on society, and despite the measures taken by transport authorities, numbers still are of concern. As such, various studies emphasize the need for investments in the road infrastructure, vehicle safety, and enforcement measures. However, traffic and accident data are scattered among several stakeholders. Police authorities, emergency agencies, hospitals, road concessions, and the national road safety authorities all hold partial data about accidents and their consequences related to human lives. If such data could become widely available on production time, e.g., when an emergency doctor reports injuries or deaths, a police officer registers the scenario, etc., intelligent analytics could be used on such data towards helpful decision support. To cope with the wide diversity of data sources and ownership, more than data integration, this requires an approach for collaborative data management. Based on previous work on strategies to structure computing and communication artifacts and data science management, we present and discuss a collaborative traffic data management strategy considering the data producers as part of an intelligent traffic collaborative network. The challenge is thus to rethink traffic and accident data collection and management under the responsibility of diverse organizations, keeping their processes and technology culture, but promoting sharing and collaboration. Therefore, the proposed approach considers data analysis performed through business processes executed in the context of virtual organizations.
AB - Traffic accidents have a devastating effect on society, and despite the measures taken by transport authorities, numbers still are of concern. As such, various studies emphasize the need for investments in the road infrastructure, vehicle safety, and enforcement measures. However, traffic and accident data are scattered among several stakeholders. Police authorities, emergency agencies, hospitals, road concessions, and the national road safety authorities all hold partial data about accidents and their consequences related to human lives. If such data could become widely available on production time, e.g., when an emergency doctor reports injuries or deaths, a police officer registers the scenario, etc., intelligent analytics could be used on such data towards helpful decision support. To cope with the wide diversity of data sources and ownership, more than data integration, this requires an approach for collaborative data management. Based on previous work on strategies to structure computing and communication artifacts and data science management, we present and discuss a collaborative traffic data management strategy considering the data producers as part of an intelligent traffic collaborative network. The challenge is thus to rethink traffic and accident data collection and management under the responsibility of diverse organizations, keeping their processes and technology culture, but promoting sharing and collaboration. Therefore, the proposed approach considers data analysis performed through business processes executed in the context of virtual organizations.
KW - Collaborative networks
KW - Data science and analytics
KW - Distributed systems integration
KW - System of systems integration
KW - Virtual organizations
UR - http://www.scopus.com/inward/record.url?scp=85138998264&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-14844-6_19
DO - 10.1007/978-3-031-14844-6_19
M3 - Conference contribution
AN - SCOPUS:85138998264
SN - 978-3-031-14843-9
T3 - IFIP Advances in Information and Communication Technology
SP - 230
EP - 241
BT - Collaborative Networks in Digitalization and Society 5.0
A2 - Camarinha-Matos, Luís M.
A2 - Ortiz, Angel
A2 - Boucher, Xavier
A2 - Osório, A. Luís
PB - Springer
CY - Cham
T2 - 23rd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2022
Y2 - 19 September 2022 through 21 September 2022
ER -