Information recycling preserves the value of our “brain material”

The information attached to a product is just as valuable as its components, explain STAR Group's Josef Zibung and Kristin Radlmayr

Transcript

Knowledge and information is quickly becoming the competitive asset. Every day we’re manufacturing more and more data; STAR Group offers a number of innovative ways to handle and access that data. Josef Zibung and Kristin Radlmayr explain what they mean by “information recycling” – making sure the intellectual material attached to recycled components doesn’t get lost – and how embedding this brain material in a semantic information model can save time and money.

European CEO: You promote information recycling as the most efficient and effective way of managing data; what does this mean?

Josef Zibung: When we speak about product lifecycle, it’s absolutely normal today that raw material is recycled in the product lifecycle. More and more the industry we observe that the industry tries to recycle complete components of products: not only the raw material, but recycle whole components. And add innovation to these components – and from the combination of these components, making new products.

The same way as components can be recycled, the information linked to those components needs also to be recycled. This information generally is not so easy to create – it’s a big work, it’s more expensive than raw material, in general. It’s our brain material. And recycling this type of information is a very good asset for all industry companies.

European CEO: So there’s three big themes you identify around information recycling; what’s the first one?

Josef Zibung: The reuse of already approved content – the maximal use of that – according to the single source principle that already elaborated and approved content is stored and reused, depending on the case. And only the new parts content is created.

The second aspect is to track all the information requests from the information consumers. According to these requests you can find out which information is really needed, and so we can put the focus on components where the most information needs exist.

The third point is give to whatever type of consumers with different skill levels, to give them personalised information. STAR has created branch-specific and also product-specific and topic-specific semantic information models. They are valid for all languages, and allow us to retrieve very specific questions to the information pool. So we can deliver personalised content to a lot of people, from different skill levels, automatically, to the needed requested information, up to date.

You have a high consistency of information, you have high quality of information due to the single source principle. It doesn’t have errors because of copying or whatever. The whole thing is taking less time. It means you have up to date information much more quickly. And naturally it costs less.

European CEO: Kristin – one area where there’s an overwhelming amount of information is in the field of technology and engineering. So how can STAR Group help?

Kristin Radlmayr: Our mission is to connect visions, technologies, and customers, for global players. This means that we want to close the gap between individual skills and technologies. We would like to help people to overcome language barriers, and to establish the basis for bi-directional communication. And the third thing we want to help with is integrate our technologies with qualified customer data to prepare them for mobile devices.

So for any kind of mobile device – not only mobile phones, but also for tablets, wearables like HoloLens and so on.

European CEO: So is this still in development or is this already live in the world?

Kristin Radlmayr: No – this has already become live. We are actually working on real customer projects. Our development team is actually implementing solutions with augmented reality. Information recycling is not something new for STAR. We have already developed products in the past: language technology products. Within this product range we have products for translation recycling, translation memories, also for technology recycling.

We have now a new product for MT translation. That means we can train engines with corporate and brand specific material, and provide this data to the customer to be used in the translation process, or also to be used by our web-based applications.

European CEO: And Josef, what’s the future of this technology? Where do you see the potential?

Josef Zibung: The future I think is speaking with products, and the product is answering! It’s beautiful: if in the morning instead of having all these messages on the coffee machine, the coffee machine sees your face and says, ‘Ah, you are Mr So-and-so; normally you are taking the espresso coffee, it’s already done, here. If you wish another coffee, please: give us the information.’

And I think with all these possibilities today, in augmented reality, in virtual reality, in simulation. I think in the future you will imagine a product… and the product is done. Years ago, nobody was thinking about 3D printing, that individuals at home can think products make them as hardware available, yeah? So I think it’s the future: where human beings and machines are more connected. And we think that the basic way to make that work, to have the profit of that, is to use our semantic technology.

European CEO: Josef, Kristin – thank you.

Kristin Radlmayr: Thank you.

Josef Zibung: Thank you also.

 

Information recycling preserves the value of our “brain material”

The information attached to a product is just as valuable as its components, explain STAR Group's Josef Zibung and Kristin Radlmayr

 

Knowledge and information is quickly becoming the competitive asset. Every day we’re manufacturing more and more data; STAR Group offers a number of innovative ways to handle and access that data. Josef Zibung and Kristin Radlmayr explain what they mean by “information recycling” – making sure the intellectual material attached to recycled components doesn’t get lost – and how embedding this brain material in a semantic information model can save time and money.

European CEO: You promote information recycling as the most efficient and effective way of managing data; what does this mean?

Josef Zibung: When we speak about product lifecycle, it’s absolutely normal today that raw material is recycled in the product lifecycle. More and more the industry we observe that the industry tries to recycle complete components of products: not only the raw material, but recycle whole components. And add innovation to these components – and from the combination of these components, making new products.

The same way as components can be recycled, the information linked to those components needs also to be recycled. This information generally is not so easy to create – it’s a big work, it’s more expensive than raw material, in general. It’s our brain material. And recycling this type of information is a very good asset for all industry companies.

European CEO: So there’s three big themes you identify around information recycling; what’s the first one?

Josef Zibung: The reuse of already approved content – the maximal use of that – according to the single source principle that already elaborated and approved content is stored and reused, depending on the case. And only the new parts content is created.

The second aspect is to track all the information requests from the information consumers. According to these requests you can find out which information is really needed, and so we can put the focus on components where the most information needs exist.

The third point is give to whatever type of consumers with different skill levels, to give them personalised information. STAR has created branch-specific and also product-specific and topic-specific semantic information models. They are valid for all languages, and allow us to retrieve very specific questions to the information pool. So we can deliver personalised content to a lot of people, from different skill levels, automatically, to the needed requested information, up to date.

You have a high consistency of information, you have high quality of information due to the single source principle. It doesn’t have errors because of copying or whatever. The whole thing is taking less time. It means you have up to date information much more quickly. And naturally it costs less.

European CEO: Kristin – one area where there’s an overwhelming amount of information is in the field of technology and engineering. So how can STAR Group help?

Kristin Radlmayr: Our mission is to connect visions, technologies, and customers, for global players. This means that we want to close the gap between individual skills and technologies. We would like to help people to overcome language barriers, and to establish the basis for bi-directional communication. And the third thing we want to help with is integrate our technologies with qualified customer data to prepare them for mobile devices.

So for any kind of mobile device – not only mobile phones, but also for tablets, wearables like HoloLens and so on.

European CEO: So is this still in development or is this already live in the world?

Kristin Radlmayr: No – this has already become live. We are actually working on real customer projects. Our development team is actually implementing solutions with augmented reality. Information recycling is not something new for STAR. We have already developed products in the past: language technology products. Within this product range we have products for translation recycling, translation memories, also for technology recycling.

We have now a new product for MT translation. That means we can train engines with corporate and brand specific material, and provide this data to the customer to be used in the translation process, or also to be used by our web-based applications.

European CEO: And Josef, what’s the future of this technology? Where do you see the potential?

Josef Zibung: The future I think is speaking with products, and the product is answering! It’s beautiful: if in the morning instead of having all these messages on the coffee machine, the coffee machine sees your face and says, ‘Ah, you are Mr So-and-so; normally you are taking the espresso coffee, it’s already done, here. If you wish another coffee, please: give us the information.’

And I think with all these possibilities today, in augmented reality, in virtual reality, in simulation. I think in the future you will imagine a product… and the product is done. Years ago, nobody was thinking about 3D printing, that individuals at home can think products make them as hardware available, yeah? So I think it’s the future: where human beings and machines are more connected. And we think that the basic way to make that work, to have the profit of that, is to use our semantic technology.

European CEO: Josef, Kristin – thank you.

Kristin Radlmayr: Thank you.

Josef Zibung: Thank you also.