Innovative ways for adding value

The impor­t­an­ce and added value crea­ted by inter­net-based ser­vices on the basis of intel­li­gent lin­ked data – so-cal­led smart ser­vices – is increa­sing more and more: Busi­ness models deve­lop out of data, values deve­lop from busi­ness models, growth and pro­spe­ri­ty deve­lop from values. Indus­tri­al Data Space opens up a new dimen­si­on for com­pa­nies all over the world in the fiel­ds of indus­try, ser­vices and retail, for the way they hand­le data and how they use this, the raw mate­ri­al of the digi­tal eco­no­my.

This is what turns Industrial Data Space into a success story – The most important questions and answers:

For com­pa­nies, data is only worthwhile if it can be pro­ces­sed. At the same time, a new, com­pre­hen­si­ve and gene­ral­ly accep­ted hand­ling prac­tice has to be ancho­red in the way data is uti­li­zed.

Indus­tri­al Data Space is a vir­tu­al data space which sup­ports the secu­re exchan­ge and simp­le lin­king of data in busi­ness eco­sys­tems on the basis of stan­dards and by using col­la­bo­ra­ti­ve gover­nan­ce models.

Data is only exch­an­ged if it is requested from trust­worthy cer­ti­fied part­ners. The data owner – i.e. the com­pa­ny – deter­mi­nes who is allo­wed to use the data in what way. As a result, the part­ners of one sup­ply chain have joint access to cer­tain data by mutu­al con­sent so that they can start some­thing new, deve­lop new busi­ness models, design their own pro­ces­ses more effi­ci­ent­ly or initia­te addi­tio­nal added value pro­ces­ses else­whe­re, eit­her alo­ne or toge­ther.

Indus­tri­al Data Space is par­ti­cu­lar­ly signi­fi­cant becau­se the data owners – i.e. com­pa­nies who want to pro­vi­de their data for digi­tal ser­vices – will always keep con­trol over their own data and can enforce their own data pri­va­cy gui­de­li­nes. (Key­word: “Pri­va­cy Enforce­ment”).

Data remains with its owner and is only safe­ly net­wor­ked “on demand”. It is only exch­an­ged if it is requi­red by trust­worthy cer­ti­fied part­ners. In extre­me cases the data its­elf will not be exch­an­ged, just the ana­ly­sis pro­ces­ses.

Data secu­ri­ty and data sover­eign­ty are the fun­da­men­tal cha­rac­te­ris­tics of Indus­tri­al Data Space.

Digi­ta­li­sa­ti­on is a soci­al, eco­no­mic and tech­ni­cal trend affec­ting all busi­ness sec­tors. Data is not only a result of pro­ces­ses and sta­tu­ses that are collec­ted and admi­nis­te­red, nor does it only ser­ve the pur­po­se of plan­ning resour­ces, pro­ducts or pro­ces­ses. It is much more that data its­elf has beco­me a pro­duct and forms the basis for ana­ly­ses as a busi­ness asset and stra­te­gic resour­ce for initia­ting inno­va­ti­ve added value pro­ces­ses.

Indus­tri­al Data Space gives com­pa­nies a stra­te­gic tool with which they can actively shape the way data is hand­led and form the basis for modern busi­ness models world­wi­de.

Inde­ed, the­re are alre­ady solu­ti­ons or even stan­dards for spe­ci­fic use cases at some indi­vi­du­al levels. Howe­ver, this still has not ans­we­red ques­ti­ons con­cer­ning gover­nan­ce archi­tec­tu­re.

Indus­tri­al Data Space will now pro­vi­de the first archi­tec­tu­re desi­gned toge­ther with users that com­bi­nes ever­y­thing and simul­ta­neous­ly sets up an inter­na­tio­nal­ly accep­ted stan­dard.

Indus­tri­al Data Space is the “data hin­ge” bet­ween Smart Ser­vices and Indus­try 4.0 pro­duc­tion and logistics.

Smart Ser­vices pro­vi­de com­pa­nies with the oppor­tu­ni­ty to stand out from the com­pe­ti­ti­on. But they increa­se the com­ple­xi­ty of sup­ply chains and pro­duc­tion pro­ces­ses enor­mous­ly. The solu­ti­on lies in auto­no­mi­zing and net­wor­king pro­duc­tion and logistics, i.e. indus­try 4.0.

Both need data: about custo­mers and their con­text (i.e. loca­ti­on, pre­fe­ren­ces etc.), about pro­ducts and goods. This data can now be exch­an­ged by ever­y­bo­dy, with ever­y­bo­dy in the mar­ket.

Indus­tri­al Data Space forms a foun­da­ti­on for indus­try 4.0 by enab­ling secu­re and cer­ti­fied data exchan­ge bet­ween com­pa­nies without the data owners losing sover­eign­ty, i.e. con­trol, over their own data. It the­re­fo­re helps to uti­li­se and spread smart ser­vice con­cepts.

Indus­try 4.0 is not the only topic the Indus­tri­al Data Space Asso­cia­ti­on focu­ses on. The user asso­cia­ti­on and its com­pa­nies also address the digi­tal eco­no­my in its ent­i­re­ty – indus­tries, ser­vices and the retail tra­de.

At the end of 2014, the Indus­tri­al Data Space initia­ti­ve was joint­ly set up by the Ger­man busi­ness, poli­ti­cal and rese­arch com­mu­nities and ever sin­ce it has been pur­suing its objec­tive to esta­blish both deve­lop­ment and uti­li­za­ti­on at both Euro­pean and inter­na­tio­nal levels.

The epony­mous rese­arch pro­ject of the Fraun­ho­fer-Gesell­schaft spon­so­red by the Federal Minis­try of Edu­ca­ti­on and Rese­arch (BMBF) aims at deve­lo­ping a refe­rence archi­tec­tu­re model for Indus­tri­al Data Space and pilo­ting it in selec­ted use cases.

As a user asso­cia­ti­on the Indus­tri­al Data Space Asso­cia­ti­on rep­res­ents com­pa­nies‘ inte­rests. In par­ti­cu­lar, the asso­cia­ti­on iden­ti­fies, ana­ly­ses and eva­lua­tes the com­pa­nies’ requi­re­ments for Indus­tri­al Data Space and sup­ports the deve­lop­ment of the refe­rence archi­tec­tu­re. It is in clo­se and direct con­tact to the rep­re­sen­ta­ti­ves of the BMBF rese­arch pro­ject.

You will find detail­ed infor­ma­ti­on, in par­ti­cu­lar about the tech­no­lo­gi­cal core of Indus­tri­al Data Space, in the WHITE PAPER.

Key elements

Sover­eign, secu­re, simp­le– find out more about the key ele­ments of the Indus­tri­al Data Space,

the inter­na­tio­nal „Net­work of Trusted Data“.

A competitive advantage

Whe­ther in indus­try, ser­vices or the retail tra­de, today, data secu­ri­ty and digi­tal sover­eign­ty are extre­me­ly important for all busi­ness sec­tors. This is whe­re com­pa­nies will find the most poten­ti­al for Indus­tri­al Data Space:

  • Bin­ding com­mon rules for coope­ra­ti­ons bet­ween part­ners
  • Par­ti­ci­pa­ti­on in an inte­gra­ti­ve, natio­nal­ly and inter­na­tio­nal­ly valid con­cept
  • Data secu­ri­ty when coope­ra­ting with part­ners
  • Trans­pa­rent infor­ma­ti­on when coope­ra­ting with part­ners
  • Homo­ge­nous data inte­gra­ti­on
  • Indi­vi­du­al manage­ment of data
  • Con­sis­ten­cy for all pro­ces­ses towards sup­pliers and custo­mers
  • Deve­lop­ment of new busi­ness models
  • Deve­lop­ment of new use cases with regard to the sharing eco­no­my
  • Deve­lop­ment of new smart ser­vices, ever­y­whe­re at any time

From practice, for use in practice

Data is the result of pro­ces­ses and it enab­les pro­ces­ses. Howe­ver, data also enab­les pro­ducts and is beco­m­ing a model its­elf. Indus­tri­al Data Space makes data acces­si­ble – learn more about three exem­pla­ry use cases that can be trans­fer­red to com­pa­nies in the fiel­ds of indus­try, ser­vices and the retail tra­de.

HIGH PERFORMANCE SUPPLY CHAINS

In many sup­ply chains, on the one hand, too much data is stored – becau­se it is red­un­dant, and on the other hand too litt­le data is stored, becau­se cer­tain data is not avail­ab­le at all levels of the sup­ply chain. That leads to deli­very risks, back­up stocks and increa­sed pro­cess costs.

This is what Indus­tri­al Data Space deli­vers.
Data exchan­ge bet­ween com­pa­nies along the sup­ply chain is stan­dar­di­sed and sim­pli­fied: a ran­ge of data from dif­fe­rent sta­ke­hol­ders can be made avail­ab­le for each other and lin­ked. That makes it pos­si­ble for pro­ducts to be traced, for trans­port ser­vices to be opti­mi­sed and to make bet­ter fore­casts for order and pro­duc­tion volu­mes.
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Use case.
Con­trol­ling trucks in inbound logistics.

LIFE SCIENCES
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Becau­se of their hete­ro­gen­ei­ty and sen­si­ti­vi­ty, data from medi­cal stu­dies has only been con­so­li­da­ted at a few spe­cial loca­ti­ons so far. Howe­ver, this can have a nega­ti­ve effect on the deve­lop­ment of new tre­at­ment methods and the evi­dence of their effec­tiveness.
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This is what Indus­tri­al Data Space deli­vers.
Data from dif­fe­rent sources can be aggre­ga­ted – taking account of the essen­ti­al need for anony­mi­za­ti­on – and trans­for­med for fur­t­her ana­ly­sis. The novel com­bi­na­ti­on of various data sources makes it pos­si­ble to cor­rob­ora­te hypo­the­ses bet­ter and fas­ter. Cli­ni­cal stu­dies can be acce­le­ra­ted and exch­an­ging the results of stu­dies can be encou­ra­ged.

Use case.
Deve­lo­ping medi­cal and phar­maceuti­cal pro­ducts.

TRAFFIC MANAGEMENT
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Envi­ron­men­tal con­di­ti­ons during the trans­port of cri­ti­cal goods – tem­pe­ra­tu­re, humi­di­ty, vibra­ti­ons or light – are regis­te­red by a wide ran­ge of sen­sors today. But how can this data be made avail­ab­le ade­qua­te­ly for custo­mers, sup­pliers and, if necessa­ry, third-par­ties?
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This is what Indus­tri­al Data Space deli­vers.
Custo­mers and sup­pliers obtain access to a plat­form on which data is made avail­ab­le safe­ly and in line with requi­re­ments. This gua­ran­tees that cer­tain envi­ron­men­tal con­di­ti­ons are con­trol­led for car­goes. This crea­tes trans­pa­r­en­cy for all par­ti­ci­pants along the sup­ply chain about whe­re the car­go is loca­ted and how long which car­go is in what con­di­ti­on.

Use case.
Com­ple­te trans­port moni­to­ring.