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Name: Cees de Laat
Affiliation: University of Amsterdam
Email:
C.T.A.M.deLaat=>uva.nl
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Session Abstract: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) projects.
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://dl4ld.nl/
Program:
- 10h45 Cees de Laat, University of Amsterdam
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- 10h50 Leon Gommans, Air France KLM & UvA
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- 11h15 Panel of stakeholders
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- Flash talks (~3 min each):
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- Craig Waldrop (EQUINIX):
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- David Groep (NIKHEF):
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- Rodney Wilson (CIENA):
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- Leon Gommans (KLM):
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- 11h30 Panel discussion moderated by Cees de Laat
- 11h45 End of session.
After the session we will present small demo's about our Docker approach.
Background information:
- Study on data sharing between companies in Europe
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- 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."
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- Trusted Big Data Sharing; Researching alliances and infrastructure models across multiple autonomous organizations presentation.
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- 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:
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- Lukasz Makowski, Daniel Cabaca Romao, Cees de Laat, Paola Grosso.
Our
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:
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- Leon
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.
Data
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 facilities. See:
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- Light Paths and Data Transfer Nodes for Aircraft Maintenance; Data Transfer Node (DTN) Workflows. - demo @ SC17:
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- Joseph Hill, Gerbenvan Malenstein, Leon Gommans, Cees de Laat, Paola Grosso.
Air
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:
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