Next to data intensive science, industry is also facing exponentially growing rates of data generated by sensors
placed in equipment, vehicles, manufacturing plants, refineries, etc.
Considering such use-cases, whilst bringing them alongside solutions serving science, provides an excellent
opportunity to learn from each other an increase the wealth of requirements.
An important challenge both science and industry faces concerns how infrastructures should consider
data-ownership rights whilst enabling the creation of value from sharing data. Organizations, that normally
compete with each other, increasingly find the need to share data to accomplish common goals no single
organization can create on its own. Such data sharing is hindered by the absence of trust among those
organizations that shared data will only be used for the purpose for which it is shared but not for other
(competitive, litigation,etc.) purposes. Examples of such use cases can be found in science (life sciences),
industry (preventive maintenance, health), and society (smart city, decision support on crowd management)
In this session, we will introduce the concept of a digital marketplace that enables an ecosystem driven by
agreements and compliance arranging exchange of data. Such ecosystem supports enforcement features that allow
organizations to manage and control risk, and therefore trust, when providing data for commonly used
applications or application development. The concepts introduced here build upon internet exchange models and
raise the peering models to the data layer.
This session will have several speakers presenting the needs from the Industry and the Science domain. Then, we
will have speakers present the architectural and methodological challenges of building such infrastructure to
support Digital Marketplaces. The session will include demonstrations of Data Marketplace principles for
preventive maintenance in the Airline Industry. Here terabytes of data must be shared in secure and trusted
environments allowing experts to monitor health of Aircraft systems like its engines. Potentially we will also
demonstrate Container Networks that create secure overlay infrastructures to invoke and enforce data policy.
Much of this work can be seen at http://sc.delaat.net and http://delaat.net/dl4ld.
All slides shown in the session are concatenated in one pdf and can be found here: NOT YET ;-)
After the session we will present small demo's about our Docker
- 10h45 Cees de Laat, University of Amsterdam
- 10h50 Leon Gommans, Air France KLM & UvA
- 11h15 Panel of stakeholders
- Flash talks (~3 min each):
- Craig Waldrop (EQUINIX):
- David Groep (NIKHEF):
- Rodney Wilson (CIENA):
- Leon Gommans (KLM):
- 11h30 Panel discussion moderated by Cees de Laat
- 11h45 End of session.
- Study on data sharing between companies in Europe
- Report from NWO/STW Workshop “ICT with Industry 2016” Lorenz Centre Leiden, Nov. 7-11th 2016; Prof. dr.
Tom M. van Engers (UvA), Prof. dr. Robert Meijer (UvA, TNO), Dr. ing. Leon Gommans (Air France KLM Group ICT
Technology Office R&D, UvA), Dr. Kees Nieuwenhuis (Thales Nederland B.V., CTO Office), "Trusted Big Data
Sharing for Aircraft MRO using a Secure Digital Market Place mechanism."
- Trusted Big Data Sharing; Researching alliances and infrastructure models across multiple autonomous
- Leon Gommans, Ameneh Deljoo, Ralph Koning, Ben de Graaff, Tristan Suerink, Gerben van Malenstein, Axel
Berg, Erik Huizer, Rob Meijer, Tom van Engers, Cees de Laat.
This effort researches the concerns many organizations have that prevents them from sharing their Big Data
Assets considering the associated risks. We show how some of these concerns can be addressed by creating
an alliance organizing and maintaining trust amongst members of a group that see a particular common
benefit. We also consider a number of Big Data Sharing infrastructure models, implementing alliance rules
using a common digital marketplace to administer and enforce them.
- DockerMon: Bring your own container - demo @ SC16:
Makowski, Daniel Cabaca Romao, Cees de Laat, Paola Grosso.
research on container-based remote data processing investigates the applicability of container
technologies for sharing of (scientific) data. We focus in particular on the analysis of the challenges
and requirements posed to the overlay networks interconnecting the containers.
Scientific datasets are usually made publicly available, however, the data cannot always leave the
organization premises. Moreover, on-site data processing can be challenging because of
incompatibility of systems, lack of manpower or the volume of the dataset itself.
We develop a proof-of-concept employing containers performing data retrieval and computation networked
with VXLAN overlay. The user is given the ability to create containers equipped with the chosen set of
functions. Where each function is capable of returning a different subset of information. Next, the
copies of the container are concurrently executed at the different locations holding diverse datasets.
The output of such execution is the data found by a particular function. Finally, the multiple results
are correlated and returned to the user.
Our SC16 demo is a gamification of the remote dataset processing architecture. The selection of
container functions is constrained by the budget i.e. each function costs a certain amount of money.
Additionally, the ability to run the created container at a selected location also requires a fee. The
user picks different search functions, represented as tools, to find animals in the remote datasets.
Lastly, correlating found animals according to the correlation method of choice. See:
- Unlocking the Data Economy via Digital Marketplaces; Researching governance and infrastructure patterns in
airline context. - demo @ SC17:
Gommans, Ameneh Deljoo, Joseph Hill, Paola Grosso, Lukasz Makowski, Gerben van Malenstein, Dirk van den
Herik, Wouter Kalfsbeek, Teresa Bartelds, Axel Berg, Cees de Laat, Robert Meijer, Tom van Engers.
sharing and digital collaboration in logistics is important for increasing efficiency, lowering costs
and lowering pressure on infrastructure and environment. Furthermore, digital collaboration makes the
creation of new logistic concepts possible, leading to new business opportunities and providing
solutions for challenges like visibility of goods, synchronization of planning among partners and
bundling of capacity. A data infrastructure must be established where data sharing among logistic
partners is easy and robust and can be set up in an ad-hoc fashion. Agreements for data sharing between
partners are secured in the infrastructure, data owners have full control over who has access to what
data and for what purpose and a service industry has arisen that offers logistic and infrastructure
services on the infrastructure. The infrastructure will maximize business value, comply with various
legal requirements whilst allowing partner autonomy, and enhance existing data sharing and storage
- Light Paths and Data Transfer Nodes for Aircraft Maintenance; Data Transfer Node (DTN) Workflows. -
demo @ SC17:
Hill, Gerbenvan Malenstein, Leon Gommans, Cees de Laat, Paola Grosso.
France-KLM uses a 100 Gbit/s link, connected to Netherlight, to research an aircraft maintenance
industry use case. Via this open exchange, Data Transfer Nodes (DTNs) of Air France-KLM in the
Netherlands and iCAIR – present in Chicago at StarLight – connect to each other using light paths over
their links. In this demonstration, users at SC’17 in Denver will experience the difference in transfer
rates with and without using DTNs. See: