Mana­ging data is a major suc­cess fac­tor for logistics com­pa­nies. As logistics rep­res­ents a key disci­pli­ne for imple­men­ting Indus­try 4.0, it needs to beco­me even more digi­tal and data-dri­ven than it is today. This invol­ves, for examp­le, by means of data sci­ence and machi­ne lear­ning, allo­wing logistics com­pa­nies to opti­mi­ze both their inter­nal pro­ces­ses and their custo­mers’ sup­ply chain.

Howe­ver, the data infra­st­ruc­tu­re of the logistics indus­try is cha­rac­te­ri­zed by a lar­ge num­ber of local data islands, making it dif­fi­cult to inte­gra­te the data and crea­te busi­ness value from it. As a result, a lot of poten­ti­al in cross-com­pa­ny or col­la­bo­ra­ti­ve pro­ces­ses in the sup­ply chain can­not be lever­aged. The aim of the Inter­na­tio­nal Data Spaces (IDS) is the estab­lish­ment of a vir­tu­al space for the stan­dar­di­zed, secu­re exchan­ge and tra­de of data while kee­ping full sover­eig­n­ty over it. For this pur­po­se, a scala­b­le and secu­re archi­tec­tu­re, that is based on modern IT tech­no­lo­gies, has been pro­po­sed.

Becau­se logistics crea­tes and con­nec­ts glo­bal value chains, its need for stan­dar­di­zed and secu­re infra­st­ruc­tu­re to exchan­ge data is extra­or­di­na­ri­ly high. Lever­aging the IDS for the logistics indus­try demands for a domain-spe­ci­fic instan­tia­ti­on that addres­ses the cha­rac­te­ris­tics and com­plex natu­re of glo­bal sup­ply chains and trans­por­ta­ti­on net­works. This is why a Logistics Com­mu­ni­ty was foun­ded wit­hin the IDSA. The com­mu­ni­ty aims at adop­ting and exten­ding the gene­ral con­cepts of the IDS to pro­vi­de a spe­ci­fic imple­men­ta­ti­on of a Logistics Data Space.

The new paper ans­wers in detail the ques­ti­on – why should the indus­tri­al data space be used in the logistics sec­tor? It illus­tra­tes chal­len­ges and poten­ti­als, pres­ents app­li­ca­ti­on models and cases in logistics.

For the posi­ti­on paper: Link