BigDataEurope SC4 Workshop: BigDataEurope and the Societal Challenge on Transport on 14th September 2017
Presentation: Data Fuelling the Disruption of Mobility
BDE_SC4_WS3_7_Josep Maria Salanova - The Mobility Use Case in ThessalonikiBigData_Europe
BigDataEurope SC4 Workshop: BigDataEurope and the Societal Challenge on Transport on 14th September 2017
Presentation: BigDataEurope Mobility Use Case in Thessaloniki
EDF2014: Talk of Krzysztof Wecel, Assistant professor, Poznan University of E...European Data Forum
Selected Talk of Krzysztof Wecel, Assistant professor, Poznan University of Economics, Poland at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Advanced Exploration of Public Procurement Data in Linked Data Paradigm
Beyond GNSS: Highly Accurate Localization for Cooperative-Intelligent Transpo...Stefano Severi
WCNC18 presentation of the results and main achievement of the EU H2020 Project HIGHTS (www.hights.eu). Take home message: accuracy is important for HAD but also robustness --> HIGHTS has developed an European Wide Service Platform for providing the best solution in term of accuracy and reliability in each context or scenario
EDF2014: Talk of Marta Nagy-Rothengass, Head of Unit Data Value Chain, Direct...European Data Forum
Invited Talk of Marta Nagy-Rothengass, Head of Unit Data Value Chain, Directorate General for Communications Networks, Content and Technology at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Collaborating on interoperability to achieve a Digital Single Market
At Finpro's seminar on May 4, Krista Huhtala-Jenks from the Ministry of Transport and Communications spoke about how the government is supporting Finland's leading position in Mobility as a Service concept.
BDE_SC4_WS3_7_Josep Maria Salanova - The Mobility Use Case in ThessalonikiBigData_Europe
BigDataEurope SC4 Workshop: BigDataEurope and the Societal Challenge on Transport on 14th September 2017
Presentation: BigDataEurope Mobility Use Case in Thessaloniki
EDF2014: Talk of Krzysztof Wecel, Assistant professor, Poznan University of E...European Data Forum
Selected Talk of Krzysztof Wecel, Assistant professor, Poznan University of Economics, Poland at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Advanced Exploration of Public Procurement Data in Linked Data Paradigm
Beyond GNSS: Highly Accurate Localization for Cooperative-Intelligent Transpo...Stefano Severi
WCNC18 presentation of the results and main achievement of the EU H2020 Project HIGHTS (www.hights.eu). Take home message: accuracy is important for HAD but also robustness --> HIGHTS has developed an European Wide Service Platform for providing the best solution in term of accuracy and reliability in each context or scenario
EDF2014: Talk of Marta Nagy-Rothengass, Head of Unit Data Value Chain, Direct...European Data Forum
Invited Talk of Marta Nagy-Rothengass, Head of Unit Data Value Chain, Directorate General for Communications Networks, Content and Technology at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Collaborating on interoperability to achieve a Digital Single Market
At Finpro's seminar on May 4, Krista Huhtala-Jenks from the Ministry of Transport and Communications spoke about how the government is supporting Finland's leading position in Mobility as a Service concept.
EDF2014: Talk of Ioannis Kotsiopoulos, European Dynamics: Semantics – Interop...European Data Forum
Invited Talk of Ioannis Kotsiopoulos, European Dynamics at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Semantics – Interoperability – Integration: A multi-faceted problem
Catch! - The project, the data & the challengePeter Lindgren
An overview of how the Catch! project is changing the way we understand how we move around our cities, so that city authorities can better meet our transport needs. A presentation by Peter Lindgren, delivered at the Catch! Transport Systems Innovation Workshop.
Catch! Workshop concept 1 - Using data to minimise the disruption of infrastr...Peter Lindgren
Team E at the Catch! Transport Systems Innovation Workshop developed a concept to use granular travel behaviour to minimise the impact of disruption on citizens from infrastructure projects.
Catch! Workshop concept 2 - Improving travel plan monitoring with better, mor...Peter Lindgren
At the Catch! Transport Systems Innovation Workshop, Team B explored how better quality travel data can deliver more effective travel planning initiatives.
BCG's new report, produced in collaboration with the World Economic Forum, describes four solutions that address the most pressing challenges in travel, transportation, tourism, and trade: http://on.bcg.com/1j7mjtO
EDF2014: Talk of Ioannis Kotsiopoulos, European Dynamics: Semantics – Interop...European Data Forum
Invited Talk of Ioannis Kotsiopoulos, European Dynamics at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Semantics – Interoperability – Integration: A multi-faceted problem
Catch! - The project, the data & the challengePeter Lindgren
An overview of how the Catch! project is changing the way we understand how we move around our cities, so that city authorities can better meet our transport needs. A presentation by Peter Lindgren, delivered at the Catch! Transport Systems Innovation Workshop.
Catch! Workshop concept 1 - Using data to minimise the disruption of infrastr...Peter Lindgren
Team E at the Catch! Transport Systems Innovation Workshop developed a concept to use granular travel behaviour to minimise the impact of disruption on citizens from infrastructure projects.
Catch! Workshop concept 2 - Improving travel plan monitoring with better, mor...Peter Lindgren
At the Catch! Transport Systems Innovation Workshop, Team B explored how better quality travel data can deliver more effective travel planning initiatives.
BCG's new report, produced in collaboration with the World Economic Forum, describes four solutions that address the most pressing challenges in travel, transportation, tourism, and trade: http://on.bcg.com/1j7mjtO
Internet for vanet network communications fleetnetIJCNCJournal
Now in the world, the exchange of information between vehicles in the roads without any fixed infrastructure is enabled thanks to the novel technology of the Vehicular adhoc networks called (VANETs).The accidents and congestions warning, Internet access e.g. via gateways along the road are the main applications of these networks related to the safety and comfort applications. A high requirement on the routing protocols is introduced in these complexed VANETs networks In order to implement a reference intelligent transportation system and contribute to the standardization of vehicle to vehicle communication or vehicle to infrastructure, in Europe, several projects are held and different partners are joined from the industry, governmental agencies and academia.This paper explains the main progress and purposes of the standardization process and research initiatives of FleetNet project. These solutions will present in the future a common worldwide VANET platform integrating several services of inter-vehicles communications.
PE01 – Perspectives and Trends
h: 9.30 am – 1.30 pm
Conference Room: Sala ROSSA
TELEMATICS PLENARY SESSION
Navigazione satellitare, infomobilità e servizi di localizzazione: trend in atto e nuove tendenze
ITS is the system defined as the electronics, advanced technology, communications or information processing used singly or integrated to enhance safety, mobility, and the economic vitality of the surface transportation system. The Intelligent Transport Systems (ITS) makes automobiles and the road traffic infrastructure intellectual and information-oriented in an integrated way to provide a safe and comfortable traffic system.
The internet of things (IoT) is a steadily growing billion-dollar market largely driven by companies undergoing digitization for greater efficiency and transparency, as well as by 5G and emerging applications like smart cities. Satellite’s inherent capabilities — such as its ability to reach remote areas, its ability to scale, to extend coverage for other providers — make it an essential part of a hybrid network needed to support an interoperable IoT system.
Traffic congestion has become one of the largest annoyances to countries like the United States and China when it comes to economic competitiveness, livability, safety, and long-term environmental sustainability. Congestion on freeways and roads is a major component of and contributor to delay. Emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), and connected vehicles provide opportunities to mitigate traffic congestion.
As one of the largest technology providers in China, Asiainfo Data is leading a city-scale Smart Transportation project in City of Wuxi, one of the national centers for IoT innovation in China. In this talk, we would like to share our real-world experiences in using AI and big data technologies to implement cutting-edge technologies transformation of Wuxi’s transportation systems. In this project, we collaborate with China Telecom, the Traffic Management Research Institute, smart vehicle makers, and many influential researchers on traffic management worldwide. We will showcase scenarios on public transportation prioritization, car-road coordination, and region-wide traffic signal optimization by utilizing AI modeling and the most advanced IoT technologies.
Speaker
Jian Chang, AsiaInfo, Chief Technology Officer
apidays Helsinki & North 2023 - Building traffic data ecosystem powered by AP...apidays
apidays Helsinki & North 2023
API Ecosystems - Connecting Physical and Digital
June 5 & 6, 2023
Building traffic data ecosystem powered by APIs
Janne Lautanala, Chief Ecosystem and Technology Officer at Finntraffic
-------
Check out our conferences at https://www.apidays.global/
Do you want to sponsor or talk at one of our conferences?
https://apidays.typeform.com/to/ILJeAaV8
Learn more on APIscene, the global media made by the community for the community:
https://www.apiscene.io
Explore the API ecosystem with the API Landscape:
https://apilandscape.apiscene.io/
Big Data Europe SC6 WS #3: PILOT SC6: CITIZEN BUDGET ON MUNICIPAL LEVEL, Mart...BigData_Europe
Presentation at the Big Data Europe SC6 workshop #3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference: BDE PIlot Societal Challenge 6: CITIZEN BUDGET ON MUNICIPAL LEVEL by Martin Kaltenboeck (Semantic Web Company, SWC).
Big Data Europe SC6 WS #3: Big Data Europe Platform: Apps, challenges, goals ...BigData_Europe
Talk at the Big Data Europe SC6 workshop number 3 taking place on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference: The Big Data Europe Platform: Apps, challenges, goals by Aad Versteden, TenForce.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
BDE SC3.3 Workshop - Options for Wind Farm performance assessment and Power f...BigData_Europe
Options for Wind Farm performance assessment and Power forecasting (Mr. A. Kyritsis, ALTSOL/TERNA) at the BigDataEurope Workshop, Amsterdam, Novermber 2017.
Big Data Europe: Workshop 3 SC6 Social Science: THE IMPORTANCE OF METADATA & ...BigData_Europe
Big Data Europe: Workshop 3 SC6 Social Science - 11.09.2017 in Amsterdam, co-located with SEMANTiCS2017 titled: THE IMPORTANCE OF METADATA & BIG DATA IN OPEN SCIENCE. Slides by Ivana Versic (Cessda) and Martin Kaltenböck (SWC)
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
BDE_SC4_WS3_2_Maria Rautavirta - Data Fuelling the Disruption of Mobility
1. Data fuelling the disruption
of Mobility
Big Data in Transport 14.9.2017
@mrautavirta
maria.rautavirta@mintc.fi
Senior Engineer, Deputy Head of Unit Maria Rautavirta
2. • Transport markets
(de-)regulation
• Involvement of
stakeholders
• Mobility as a Service
(MaaS) experiments
• Strategic
guidelines and
actions
• Regulative
analysis and pilots
• My Data operating
model and pilots
• Data sharing
practices
• Data protection in
Digital business
• Endorsement of
intelligent transport
• Testing areas:
Aurora, Nordic
Way
• Unmanned
aircrafts (RPAS
regulations)
• Strategic
guidelines
• Implementation
of information
security strategy
• Implementation
of Information
Security Directive
• 5G
• Standardisation
• Promotion of optical
fibre construction
Robotisation
and
Automation
Big
Data/My
Data
Mobility as
a Service
Data
Security
Internet of
Things
+ Mid term review
• Logistics
• Data economy for
transport
• Satellite navigation
3.
4.
5. Transport code – Transport’s Bit Bang
Legal provisions on transport market brought together under the Act on Transport Services. Aim is to support new service models and to better
meet user needs. Further aims are to review the transport system as a whole, make market access easier and promote interoperability.
Data interfaces
Regardless of the transport mode, a passenger
mobility service provider shall ensure that essential
data of the service is available. The essential data
concerned is specified in a government decree.
Sales interfaces
Road and rail passenger transport, and brokering &
dispatch services providers, or actors managing a
ticket or payment system on their behalf, shall give
mobility service providers and providers of
integrated mobility services access to the sales
interface of their ticket & payment systems. The API
must enable the purchase of a ticket product that,
at minimum, entitles to a single trip or reserve a
single trip or transportation service.
6.
7. Traffic
control
e-CMR and agreement
data (DTLF SG1,
UNECE/CEFACT)
DTLF
Digital Transport and
Logistics Forum
C-ITS
(C-ITS
Platform,
ETSI)
E-Manifest –
(UCC ja FAL-
agreement)
Maritime
European
Maritime Single
Window
SafeSeaNet
Service
providers
DTLF model
infrastructure for data
sharing
V2V ja V2I,
personal
data
Manufact
urer
Connected
and
automated
driving
I2V, V2X,
V2P ja
V2B(C)
Manufac
turer
V2B
(backend)
Infrastructu
re
Control/Ma
nagement
Service
providers
(RMI)
?? RMI, eCall-comm, Car2Car
Communication Consortium, 5GAA)
AccessDatastorageDatacontentFrame
FI: Portnet
Multimodal corridor data cloud (CEF)
8. Data access for Seamless and interoperable multimodal
transport services
Transport service availability data
(structured data)
Anonymous single ticket (3rd
party access to ticketing and
reservation system)
Tickets containing personal data
and subsidies (tickets with
passenger name, monthly tickets,
student tickets, liability
programmes)
Open data (open
licence)
APIs (+authentication of the
MaaS service provider)
API (Authorisation and
authentication of 3rd party
acting on behalf of the user)
API (user authentication and
permission for 3rd party to act on
behalf)
Anonymousdata
TransportCodePhaseI
Personaldata
TCPhaseII
2 years ago I was together with 7 other colleagues given a task to bring transport to the 21st century. We had a task to deliver digital growth environment for transport Sector.
This meant streamlining the transport laws and for the first time introducing data in the legal framework.
We have only 3,5 months until the requirements for data come into force and all these 2 years we have been talking about data, digitalisation, API s and we are almost understanding what data can do with us.
Government strategic key project: Building growth environment for digital business
Data is the fuel in all elements of the key projects. The also all belong to the data driven transport policy
If data is the fuel it needs to be drilled
Access to data is the critical element is dataeconomy
Access to good quality data, that is accurate and timely
data is everywhere, but structured good quality data is the key
Some data we must dig deeper
Not everybody is willing to share data and I think that many organizations do not even think that their data is valuable.
I use mobility as a service as an example
When we started
Customer
Needs services
And we have enablers and facilitators to. Promote it, infrastructure and smart payment
We have multiple services but we also have other sectors and shared assets we want to connect
To put this all togethjer we need data
We need easy access to data and little push
Transport code the Bit bang
Data is addressed in all three phases of transport code.
The phase 1 concentrates purely on the maas data
Forces to open the essential data
Forces to open ticketing API’s to third parties
And Forces data reporting, and public transport operators to realize back office support to public transport
It all means more data, specific structured data, bt also big data, but the key is the guaranteed access
What we then do with the data
We create architectures and structures to share and administrate accesses and liabilities in the data chain
Here are some data projects going on in the EU
In all these projects structured data has raisen essential
Data has to have certain form in order to be combined and transferred
Security
We have talked about silos as an obstacle for viabl ebusiness models and multimodality.
But what we are now generating in the transport sector is siloed data
If digital makes it easy t combine passengers and packages, the data storage, acces and sertificate policies can put us back in the silos
We cant avoid, that we have tol create solutions in different use cases, but we can at the same time create genereic models
For the phase II we’ve analysed the possibilities of extending the data provisions also to other modes such as aviation and maritime. However, the current international legislation relating to passenger data and our commitment to adhere to data protection and privacy at the highest level, does not make this possible.
At the same time, certainly all of us here acknowledge that the basic, impersonal single tickets or journeys are not the Holy Grail we are all after. They will certainly not make that behavioural change in the end—users.
However, what if we once again go back to our underlining, original thinking? What if we once again make the customer the central focus of our actions?
What if we would create a regulative framework that enables making the end-user the king of his or hers data, including having the possibilities of passing rights of reuse to other service providers?
Through the Transport Code phases I & II we could not only kick-start the true systemic level digitalisation of the transport sector but also activate a MyData revolution.
We believe that this is all doable. Such forward thinking regulative measures are not unprecedented even on the EU level. Think for example what is currently being done in the banking sector with the EU’s renewed payments services directive, the so-called PSD2.
This is something we are exploring at the moment and I hope we can give more details of our plans soon enough.
Accessing we understand, but what about sharing and distributing
Here we raise the concern about privacy aghain
A human-centric approach to data management
MaaS operator as a MyData operator
Turning data subjects’ rights into reality
Interoperability of systems
GDPR Compatible
Recipe for good way to handle data
Security by design
Safety by design
Open by default
And user in the center
We see that only open ecosystems can thrive competitions and innovation in a way it benefits also the societys
Ppp devolopment, smart city thinking, service design are all tools to provide services based on data
Pilots and pilots
As a conclusion
Sektorisääntelystä yleisiin ja yhteisiin periaatteisiin
Datan fyysisestä staattisesta sijainnista datan liikkuvuuteen ja dynaamiseen hyödyntämiseen
Datan omistajuudesta ja yksinoikeuksista
Jaettuihin datoihin ja hallinta ja käyttöoikeuksiin
Horizontal solutions to access and shre data
As an example:
DTLF Discussion on principals could esily be implemented in all use cases
Data should be required to be stored or delivered only once with minimal administrative burden.
Minimum data contents should be harmonized also to reflect other modes of transport whenever possible.
Data should be made available and shared with easy access (preferably APIs/interfaces) to relevant authorities and also to selected business partners or other stakeholders. User rights to access the data should recognize and respect the different levels of privacy and be reflected in the authentication protocols.
Solutions should cover all relevant stakeholders, also SMEs, implying a level playing field and open systems with solutions that are acceptable to all stakeholders (e.g. low cost, easy to use, easy of deployment). Technical solutions and systems should be built modular and interoperable and utilize open source solutions whenever possible. In addition to the general minimum requirements, companies and authorities should be able to complement their particular solutions while maintaining the interoperability within this open environment.
To fully benefit the potential of Big Data, data should be made available as openly as possible. Solutions should be developed so that also business and stakeholder relevant data could be shared for instance through anonymizing.