personalised public services, using open data and services, enhancing transparency and decision-making processes of public administrations,
Against the update of structural data, the project will test these hypotheses on the qualitative impacts of the Third Sector in terms of capital building (e g. social networks,
1) increased digital information and controls; 2) dynamic optimization of grid operations, including cyber security; 3) deployment of distributed resources, including renewable resources;
and generated energy data along with actionable commands to customers. With technologies such as WIFI Zigbee, and home area network (HAN) communication systems, smart meters can now act as interfaces for energy management entities, customers,
Data management is critical for the widespread operation of the smart grid in the near future
Reconfiguring the system in islanded mode may require hitherto unknown rate and amount of data exchange, two-way communication links,
IEEE Standard 1451.4 requires analog sensors to have a transducer electronic data sheet to provide calibration information to the data acquisition system 37,38.
Fig. 5 shows how several communication technologies can be applied for such data, according to their characteristics.
and storage must be implemented in a platform that allows both digital information and electric energy to flow through a two-way smart infrastructure.
eventually making possible the creation of an open-access same-time information system†a Web-based secure database of transmission-system-related information.
Data Sheet (TEDS) Formats, IEEE Standard 1451.4-2004, Dec. 2004.38 Q. Zou and L. Qin, â€oeintegrated communications in smart distribution grid, â€
In a survey of European SME perspectives on cloud computing, the security of corporate data and potential loss of control featured highly among the concerns for SME owners (ENISA 2009),
even though 49%of SMES already exchange data in an automated fashion with other ICT systems outside their own enterprise (Giannakouris and Smihily 2010).
questions and lessons learnt for SMES based on the existing resources, notably specific assessment tools, checklists and databases,
and improving the data management of the chemicals2. www. aga. com CAR2GO: selling new forms mobility The â€oenext step†for car-sharing models may be the concept of CAR2GO.
database including carbon footprint data of over 300 materials, energy carriers, and delivery of waste treatment and transport lca. jrc. ec. europa. eu/lcainfohub/datasetarea. vm Guide to PAS 2050†How to assess the carbon footprint of goods and services shop
Energy productivity expresses the amount of economic value generated by one unit of energy input or consumption. 5 SERI 2011, Global Material Flow Database. 2011 Version. www. materialflows
EIO 2012 based on data from Demea (N=92) Figure 6: Yearly savings potential in SMES introducing material efficiency solutions Eco-innovate production processes Eco-innovate!
closed-loop energy system Electroself (Italy) is an enabling technology for distributed energy that self-generates its own fuel and guarantees backup power in remote areas.
The most in demand information includes data on the origin of resources used in products and evidence on the social and environmental impacts of resource use across the supply chain. 3. 3 Supply chains Supply chain management includes coordination and collaboration with suppliers,
A guide to eco-innovation for SMES and business coaches. 41 eco-innovation observatory MATREC materials database showcases developments in new,
page 44) What data and tools are available to assess •the (quantified) environmental impacts in Key challenges for your business Design may be performed by product design-•ers, design engineers,
Communicating data or information on a •product†s environmental impacts is not always a strong motivator for customers
a cleaner printed cicruit board Crawford Hansford & Kimber developed a †cleaner†printed circuit board (PCB) that is incorporated into equipment that interfaces with data loggers that is now in use in higher education around the world.
How do we incorporate environmental performance related data in communications? What is the product†s Unique Selling Proposi-•tion (USP) relative to competitive offers?
Have you got evidence to backup your claims? Greenwashing must be avoided! How are you going to create â€oenoise†in the •market and amongst your customers?
a repository of good practices and online database. www. eco-innovation. eu INNOWATER is a public-private partnership of public innovation agencies, water associations and technology specialists
including reduction greenhouse gas emission across the life cycle of bio-based products. www. biochem-project. eu The European commission has funded a range of projects collecting data and good practice examples
 EIO 2012 based on data from Demea (N=92) p. 28: Source:  www. lisec. com/LPS/Glas-Vorspannanlagen-speziell-fuer-Duennglas p. 29:
Visit our website to get open access to our reports, interactive database with charts and maps,
meaning internet connections, web collaborative tools, sharing of open data and a process of bottom-up peer-supported activities and applications.
Examples are given on the novel use of information platforms, data from sensor networks and community use of mobile phones.
Our data comes from the EU activities and R&d grants awarded up to 2014. We describe the concept, the context,
to support stronger links (data exchange, visualization) and thus to multiply the potential effect of grass-root initiatives.
namely to set up Internet platforms and digital information processing tools to promote those value-generating collaborations
crowdsourcing and crowdfunding, big data visualisation and analytics, P2p production and consumption, edemocracy and eparticiaption. Crowdsourcing refers to a platform for on-line distributed problems and a network of coordinated human †problem solversâ€.
This study, in fact, mapped 590 organisations with 645 projects active in the filed across Europe (data of August 2014.
Actors and initiatives were crowd-mapped trough the project platform digitalsocial. eu were data are updated constantly.
the â€oeself-assessment toolkit†(SAT) and the â€oeuser Data Gathering Interphase†(UDGI. The first one is dedicated to CAPS projects coordinators and partners and the second one to CAPS users.
and human capital because its outputs and its activities are not leading to this kind of impacts. 5. At this point the SAT will show all the questions related to the impact dimensions selected by the project representatives. 6. The data inserted by CAPS representatives will be elaborated in real time by the SAT
IA4SI team will use all the gathered data for developing two impact assessment reports: one will include the assessment of each CAPS project
and one will analyse the data at aggregated, domain level. Besides this, a set of best practice will be identified
that more diverse sources of data improves impact measurement, but that ultimately it is stakeholder engagement that makes the difference to sustainable social innovation.
Twenty-first century social science needs to have access to new data gathering resources to collect to sample to validate hypotheses
The open data portal is experimenting with this distributed data resource. The findings can be reapplied to generate more collective intelligence.
"Guidelines for Collecting and Interpreting Innovation Data Passani A.,Monacciani F.,Van der Graaf S.,Spagnoli F.,Bellini F.,Debicki M,
by further developing instruments that allow for aggregation of local initiatives, such as clustering, to really unlock the potential of innovative SMES.
Available data are not reassuring. As shown below, in Figure 1, the gap between the EU15 and the United states in terms of expenditure in R&d has been in place since the early 1980s.
Kristian Uppenberg, presentation at the first Task force meeting, 18 september 2009, OECD data. 14 INTRODUCTION. TOWARDS EUROPE 2020 An important issue is the ability of the European Investment Bank (EIB) to reach dynamic and innovative small firms
such as clustering, to unlock the potential of innovative SMES. This constraint reflects a more general situation,
Section 6 briefly concludes. 27 2. A NEW APPROACH TO INNOVATION POLICY IN THE EU 2. 1 Innovation is a changing concept The data reported in the previous section show that Europe is facing a structural problem
Available data testify to a European †lag†vis-Ã-vis the United states, Asia and several emerging economies in terms of research, development and innovation (R&d&i.
Available data 6 See European Innovation Scoreboard 2009 at http://ec. europa. eu/enterprise/newsroom/cf/document. cfm?
Also, European companies perform about 30%of R&d outside the EU. Data presented at the Task force meetings are based on evidence of collaboration between EU
by further developing instruments that allow for aggregation of local initiatives, such as clustering, to really unlock the potential of innovative SMES. 2. 2. 2 A coordinated,
and data using common indicators. 2. 2. 3 Taking innovation seriously: improving governance through accountability and coordination Putting innovation at the core of the EU policy-making process cannot only be a declaration of intent.
Such data shows that companies with a large share of their business in the US or Japan receive a substantial advantage from their own patent 17 As a matter of fact,
p. 25.24 Data are available in the Communication from the Commission to the European parliament and the Council Enhancing the patent system in Europe, COM (2007) 165 def, p. 7. A NEW APPROACH TO INNOVATION POLICY IN THE EUROPEAN UNION 47 case of SMES.
together with studies and empirical data provide useful inputs for policy decision regarding a future patent system,
and available empirical data on the fact that European universities are good at sciences and technology,
LTE IPR declarations on the ETSI database are 1, 860 as of January 11th, 2010. The following graph exemplifies the number of IPR declarations on the LTE project.
and an important feature for building up IPR databases at SSOS o Ex-Ante Disclosure of FRAND licensing Promise is important for necessary privilege under Art. 101 (3) EC Treaty as every
New emerging technologies like smart materials, micro-mechanical sensors and wireless and faster data transfer solutions etc. have presented new opportunities to develop product features, especially those intangible features
and PDM (Product Data Management) can be used to manage product-related information. The main point is that ICT should fully support the business processes
for example Business intelligence solutions to manage business data and information from marketing and customers. Markets are providing a huge number of different solutions to different needs,
Companies should clarify their data administration vision: which kind of solutions best fits the company and
However, there were insufficient data on the cost-effectiveness of these systems and it was not possible to determine the extent to which the demonstrated benefits were generalisable.
and to create data exchange networks is more straightforward. Another structural barrier is the lack of standardisation and certification for EHR and health IT systems
resulting in the lack of system and data interoperability. A contributing factor to the delayed standard adoption is the lack of incentive for data exchange between and among providers as well Kaye, Kokia, Shalev, Idar and Chinitz 166 Â W s. Maney & Son
Ltd. 2010. Journal of Management & Marketing in Healthcare. VOL. 3 NO. 2. PP 163†175.
and confidentiality are also often barriers to health IT as they tend to restrict the sharing of patient data among providers.
better care based on better documentation and better management of resources based on better data. Over time, these goals were expanded
Miller and Sim identified seven major doctor-related barriers: high initial financial costs and uncertain financial benefits, high initial physician time costs, difficulties with technology, difficult complementary changes and inadequate support, lack of adequate
electronic data exchange between the EHR and other clinical data systems, lack of incentives and physician attitudes. 15 On the other hand, in summarising the critical success factors Kaye, Kokia, Shalev, Idar and Chinitz
fully integrated health information and communication system with a comprehensive database that includes more than 18 years of data on almost 2 million members.
and with continuous clinical data exchange taking place in real time. This system with all of its components, was developed over a period of 20 years,
setting stringent standards that all IT vendors had to meet to assure compatibility for purposes of connectivity to enable clinical data exchange,
and to provide ongoing feedback during implementation. 2. A minimum data set was agreed upon, with the gradual addition of new fields and tools over time. 3. It was agreed at a very early stage what the doctor would see first
when he opened the EHR †a summary page with the most relevant patient data. 4. In the case of each additional field or tool,
particularly when the EHRS had the capacity to store data with high fidelity, to make those data readily accessible,
and to help translate them into context-specific information that can empower providers in their workâ€. 17
JUNE 2010 171 †the insertion of the membership card generated an online connection to the Maccabi database for verification of the patient†s eligibility to receive services,
and investment in the communication infrastructure for clinical data exchange is a must for a system that will be sustainable over time, in terms of benefit to doctors, patients and the healthcare system.
This means hotlines, backup systems and help when the doctor needs it and not when it is convenient for technical staff to provide it. â€
Miller, R. H. and Sim, I. 2004) †Physicians†use of electronic medical records: Barriers and solutionsâ€, Health Affairs, Vol. 23, No. 2, pp. 116†126.16.2005) †ehealth IMPACT †Study on Economic Impact of ehealth:
Recent calculations by the authors of this paper, based on Germany†s official â€oestatistics portal†data, show that the high percentage of SMES amongst all enterprises continues to remain high.
2 These data exemplarily demonstrate the key-role which SMES play in Germany†s economy.
The rest was rejected because of containing incomplete and/or contradictory data. Figure 3 shows the representation of the industry sectors in the sample.
confirm, or extend the data base with experts from the selected industries like firm representatives, representatives of industry associations and cluster managers.
whereby the data is transmitted electronically from one centre to next. Such a step could be of crucial importance for time-critical projects,
on the digitisation and online accessibility of culture. pdf. txt Ëj & Deloitte europe's vision and action plan to foster digital entrepeneurship. pdf. txt õ>'Design-Driven Innovation-Why it Matters for SME
-Challenges & Opportunities of Big data for the Digital Society. pdf. txt'¥ Perceivced Barriers to Innovtion in SMES. pdf. txt>Policies in support of high growth innovative smes
Newspapers Workshop. pdf. txt 8 Recommendation on the digitisation and online accessibility of cultural material and digital preservation. pdf. txt Ô Regional Planning Guidelines southeastireland. pdf
ê Using big data for the future of personal transportation DATASIM Digital Agenda for Europe Euro. pdf. txt n?
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G#2v 8552 Aheylite 0#3#aheylite Aheylite G#2v 8553 Ahlfeldite 0#3#ahlfeldite Ahlfeldite
G#2v 8554 Aikinite 0#3#aikinite Aikinite G#2v 8555 Ajoite 0#3#ajoite Ajoite
G#2v 8556 Akaganeite 0#3#akaganeite Akaganeite 0#3#akaganéite Akaganeite G#2v 8557 Akatoreite
0#3#akatoreite Akatoreite G#2v 8558 Akdalaite 0#3#akdalaite Akdalaite G#2v 8952 Åkermanite
0#3#akermanite Åkermanite 0#3#åkermanite Åkermanite G#2v 8559 Aksaite 0#3#aksaite Aksaite
G#2v 8560 Alabandite 0#3#alabandite Alabandite G#2v 8561 Alamosite 0#3#alamosite Alamosite
G#2v 8562 Alarsite 0#3#alarsite Alarsite G#2v 8563 Albite 0#3#albite Albite
G#2v 8564 Aldermanite 0#3#aldermanite Aldermanite G#2v 8565 Alforsite 0#3#alforsite Alforsite
G#2v 8566 Algodonite 0#3#algodonite Algodonite G#2v 8567 Aliettite 0#3#aliettite Aliettite
G#2v 8568 Allabogdanite 0#3#allabogdanite Allabogdanite G#2v 8569 Alloclasite 0#3#alloclasite Alloclasite
G#2v 8570 Allophane 0#3#allophane Allophane G#2v 8571 Almandine 0#3#almandine Almandine
G#2v 8572 Alstonite 0#3#alstonite Alstonite G#2v 8573 Altaite 0#3#altaite Altaite
G#2v 8574 Aluminite 0#3#aluminite Aluminite G#2v 8575 Alunite 0#3#alunite Alunite
G#2v 8576 Alunogen 0#3#alunogen Alunogen G#2v 8577 Amblygonite 0#3#amblygonite Amblygonite
G#2v 8578 Ameghinite 0#3#ameghinite Ameghinite G#2v 8579 Amphibole 0#3#amphibole Amphibole
G#2v 8580 Analcite 0#3#analcite Analcite G#2v 8581 Anapaite 0#3#anapaite Anapaite
G#2v 8582 Anatase 0#3#anatase Anatase G#2v 8583 Andalusite 0#3#andalusite Andalusite
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