'However,'the'development'of'territorial'ICT'infrastructures'(such'as'the'broadband'connection)' and'the'absence'of'a'digital'divide'are'important'determinants
data! on! the! level! of! takecup! of! ecprocurement! on! total! regional! procurement! to! promote! healthy!
'For'example,'overcoming'the'territorial'digital'divide'is'a'necessary 'but'insufficient'condition'to (become (an (adopter.'
digital divide.''''Second,'legislative'factors'are'also'critical.''Differently'from'eqprocurement,'law'imposition'is'not'so'relevant'for'the'adoption'of'telework.'
data! on! the! organizational! well! being! achievable! through! the! implementation! of! telework.''''Determinants (and (barriers (in (the (inner (context('The'inner'context'is'much'more'important'than'the'external'one'in'the'case'of'telework.'
'broadband'connection)' for'eliminating'territorial'digital'divides.''2. Elaborate'policy! guidelines'for'harmonizing'national'and'regional'laws'with'the'proposals'adopted'by'the'European'commission'in'December'2011'(IP/11/1580)' on'public'procurement's'modernization.'
data'on'the'level'of'takequp'of'eqprocurement'on'total'regional'procurement'for'promoting'healthy'competition.'
'broadband'connection)' for'eliminating'territorial'digital'divides.''2. Implement'the! European-Framework-Agreement-on-Telework-(EFAT)- at'the'national'level'according'to'the'most'appropriate'regulatory'tools'(i e.'
'and'publish'data'on'the'organizational! wellcbeing'achievable'through'the'implementation'of'telework.''5. Enhance'the'quality'and'the'quantity'of!
1 HORIZON 2020 The EU Framework Programme for Research and Innovation 3d & Cultural Assets Albert GAUTHIER DG Connect Unit G2 Luxembourg CONNECT-G2 DIGITAL CULTURE
and policy support. 2 3d& Cultural Assets Painting Statue Building Museum Books Church Monuments Archaeological Site.
3d & Cultural Heritage 3D PRINTING et COPYRIGHTS 8 15 ICT 22 R&i action (a a) RESEARCH ON COST-EFFECTIVE TECHNOLOGIES FOR ADVANCED 3d MODELLING TO ENHANCE THE UNDERSTANDING
o consolidation of imperfect data, o spatiotemporal analysis, o modelling/simulation of material degradation, o joint reconstruction within and across collections,
or generated by a wide range of devices or software. H2020 Reflective 7 b 10 19 ICT 22 R&i action (a) H2020-Reflective 7 Budget:
100%H2020 Coordination and support actions (CSA) 22 Creativity website: http://cordis. europa. eu/fp7/ict/creativity/creativity en. html Digital Agenda for Europe:
/creativity/call1-infoday en. html emails: CNECT-digicult@ec. europa. eu CNECT-Creativity@ec. europa. eu Twitter:@
@digiculteu &@ICTCREATIVITYEU 12 3d & Cultural Heritage
Europeana Newspapers Workshopmarieke Willems, LIBERMAIL: marieke. willems@kb. nlliber2013, Munich, June 26th, 2013 This project is funded partially under the ICT Policy Support Programme (ICT PSP) as part of the Competitiveness
The extent of newspaper digitisation in European Libraries Refinement Quality Assessment Metadata 2. You share with your neighbour during the Buzz3.
ideas and challenges during the panel discussionbest Practice Sharing at this Workshopimage from Library of Congress This project is funded partially under the ICT Policy Support Programme (ICT PSP) as part of the Competitiveness
The report, together with any data and indicators published therein, can be downloaded from the Kaleidoszkóp website using the following link:
http://kaleidoszkop. nih. gov. hu/3 This is Part 3 of the RDI Mirror series written under the auspices of the National Innovation Office RDI Observatory Department.
All these data are indicative of very large disparities between the country's various regions. From the point of view of the RDI, Hungary has a peculiar geographic structure,
and data promoting a better understanding of the above. 5 Introd uction...6 1. The position of Centra l Hungar y within the RDI landscape of Hungar y...8 1. 1 Disproportions within RDI measuring concentration...
Our objective is to provide an analysis of the R&d and innovation related performance and potential of particular regions, based on comparative facts and data.
Pending the availability of relevant data, provided that these were a useful source of information
as well as in the interests of the reliable interpretation and presentation of underlying statistical data. Subsequent chapters are devoted to comparing data on other regions and counties,
even though Budapest and the Central Hungary region are mentioned in this part, and moreover, in several chapters.
therefore-for the sake of a better comparison-in a number of instances we presented them among county level data streams.
Our analysis uses the latest available data: in the case of R&d this covers 2011,
however regional GDP data for 2011 are only preliminary data; other labour market data relate to 2012,
or were taken from census findings for 2011. We also deploy a number of regional econometric methods, the findings
This accounts for the slight discrepancy between the data we present in Chapters 1. 4 and 3. 7 on the one hand,
and HCSO data on the other. Census statistics provide a treasure trove of comprehensive data for our analysis,
and in our view show a strong correlation with innovation potential, examples of which are foreign language proficiency, the percentage rate of higher education graduates within the total population,
and labour activity data in general. We also did some correlation and regression analysis of innovative sectors/industries,
We compress the data streams analysed into complex indicators, in the course of which we treat the infrastructural and human resource aspects of innovation separately.
namely that with the exception of Central Hungary, we are practically unable to correlate sectoral and regional data for any other region in a way that would ensure compliance with the statistical golden rule on the traceability of the data provider.
or fewer data providers made up a group of this kind, and so pursuant to prevailing regulations we were allowed not to display their data.
This in itself clearly illustrates the current state of research and development in Hungary: stakeholders are very thinly spread in many regions and sectors/industries,
Being the case this has limited unfortunately our ability to include more data than what finally ended up on these pages,
as a result of which the depth of sectoral data suffered most of all. If this publication therefore gives the impression that it does not provide a comprehensive account in respect to the regions outside Central Hungary,
then it should be noted that the relevant data do exist, but they cannot be made public due to the above reasons.
As it was impossible to display the full array of relevant RDI data in the core text of this document many of the tables,
Based on the data of 19 counties and of Budapest itself for 2010, we may conclude that the concentration values of indicators for directly measuring R&d (0. 4 in terms of total R&d expenditure
Available data indicate a high concentration in most cases: according to preliminary data for 2011, the per capita GDP (calculated by purchasing power parity) of Budapest is more than double the national average (EU R 16,484 per capita),
representing EU R 35,583 per capita. For the same reason, the per capita GDP of Central Hungary (EU R 26,574) is significantly above the national average.
i e. statistics comprising the unique data of 19 counties and Budapest. Concentration converging to 0 indicates a diffuse, even distribution of objects designated by the indicator in question.
graphs and tables presented in this document contain data of various aggregation levels, on the understanding that these data are not always absolute figures.
The possibly most detailed and absolute data are usually found on the National Innovation Office RDI Observatory's website:
http://www. kaleidoszkop. nih. gov. hu/(provided that their publication is prohibited not due to data protection) 6 Gross Expenditure on Research and development:
means the total research and development expenditure of companies. 7 Migration balance: means the net balance of immigration and emigration during the period under review. 10 341 11 451 11 092 12 285 12 976 14 080 15 145
The National Innovation Office RDI Observatory's own calculations based on HCSO and Eurostat data 10 1. The position of Ce ntral Hungary within the RDI landscape of Hungary
The National Innovation Office RDI Observatory's own calculations based on HCSO data. In Ce ntral Hungary 2/3 of total R&d expenditure is use d by the business enterprise se ctor,
and we know that the cost effectiveness motivated process of repeated production site changes follow the same geographic pattern.
The data presented here9 demonstrate the weight of certain indicators characterising companies engaging in R&d within the central region (we also included data for Budapest and Pest County separately.
zzcf Manufacture of pharmaceuticals zzci Manufacture of computer, electronic and optical products zzcl Manufacture of transport equipment zzcj Manufacture of electrical equipment zzd Electricity, gas
zzinformation and communication services zzmanufacture of pharmaceuticals zzmanufacture of computer, electronic and optical products We may also conclude that Central Hungary does not have a significant weighting within the following sectors/industries:
and we included data for Budapest and Pest County separately. 10 The Community Innovation Survey (CIS) commissioned by the European union every two years analyses the innovation activity of companies.
The National Innovation Office RDI Observatory's own calculations based on HCSO data The relative share of the rest of the country The relative share of Pest County The relative share
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Manufacture of pharmaceuticals shows extremely high levels of concentration,
and with even higher rates of concentration recorded in the above R&d indicators. 14 1. The position of Ce ntral Hungary within the RDI landscape of Hungary The manufacture of computer, electronic and optical
Ce ntral Hungary significantly dominates the manufacture of computer, electronic and optical products compared to the country's other regions. 72,2%91,3%87,1%93,1%100%5, 6%1, 4%22,2%8, 4%10,5%2, 4%5,
The relative share of Budapest, Pest County and the rest of the country of the key indicators of companies engaging in R&d and active in the manufacture of computer, electronic and optical products sector, 2011.
The National Innovation Office RDI Observatory's own calculations based on HCSO data. The relative share of the rest of the country The relative share of Pest County The relative share of Budapest 91,3%0%10%20%30%40%50%60%70
The National Innovation Office RDI Observatory's own calculations based on HCSO data. By national comparison, Budapest and Pest County do not have a significant weight within R&d performance associated with the manufacture of electrical equipment:
The National Innovation Office RDI Observatory's own calculations based on HCSO data. 0%10%20%30%40%50%60%70%80%90
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Budapest has a dominant position within the R&d performance of the information
which can be downloaded from our website at: http://kaleidoszkop. nih. gov. hu/0%10%20%30%40%50%60%70%80%90%100%51,3%64,7%44,4%59,5
The National Innovation Office RDI Observatory's own calculations based on HCSO data. The Central Hungary region accounts for a significant proportion of professional, scientific and technical activities and although it might come as somewhat of a surprise,
In the above we provided an analysis of the status of regional concentration characterising the manufacturing industry (more particularly of manufacture of pharmaceuticals, the manufacture of computer, electronic and optical products, the manufacture of electrical equipment and the manufacture of transport vehicles
GDP per capita by county (EUR, PPP based on preliminary data for 2011. Source: The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former. 2 Capturing a snapshot of Central Hungary
and Budapest is only part of the regional aspect of RDI, but in order to see the full picture it is vital to include a description of every region.
EU R 16,484 based preliminary HCSO data for 2011. If we look at individual regions, then we find that Western Transdanubia is above the national average,
Total R&d expenditure as a percentage of GDP by county (based on preliminary GDP data for 2011.
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
By comparing the same data at a regional level, we find that apart from Central Hungary only the two Northern
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
as these indicators can tell us more about real living standards than GDP or any other macroeconomic data.
The National Innovation Office RDI Observatory's map imaging based on HCSO data. Regions other than Central Hungary employ no more than 40%of all Hungarian researchers (what is more, this value goes down to 34.2%when converted into FTE),
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former. 25 3. Innovation potential of unemployment is significantly lower for counties of the Transdanubian region
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former.
The National Innovation Office RDI Observatory's own calculations based on HCSO data. The competence assessment,
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Lecturers Students 50.8%12.2%10.1%9. 9%5. 9%5. 8%5. 3%Central Hungary Central Transdanubia Northern Hungary Northern
The National Innovation Office RDI Observatory's own calculations based on HCSO data. 3. 4 The link between national migration and R&d In recent years, national migration
data including both domestic and international migration statistics). Central Hungary has already been mentioned, other than that-compared to other counties-Gyor-Moson-Sopron stands out with an impressive positive migration balance,
and it is obvious from the migration data, that most counties with a positive balance are in the western part of Hungary,
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former. 628 165 149 143 65 54 30 0
zzcf Manufacture of pharmaceuticals zzci Manufacture of computer, electronic and optical products zzcl Manufacture of pharmaceuticals zzcj Manufacture of electrical equipment zzd Electricity, gas, steam
The National Innovation Office RDI Observatory's own calculations based on HCSO data. 17 Baranya Borsod-Abaúj-Zemplén Veszprém Csongrád Hajdú-Bihar-30
The National Innovation Office RDI Observatory's own calculations based on HCSO data for 2010. CF Manufacture of pharmaceuticals;
CI Manufacture of computer, electronic and optical products; CL Manufacture of transport equipment; CJ Manufacture of electrical equipment;
County level correlation analysis based on GEOX and HCSO data for 2010. CF Manufacture of pharmaceuticals;
CI Manufacture of computer, electronic and optical products; CL Manufacture of transport equipment; CJ Manufacture of electrical equipment;
The National Innovation Office RDI Observatory's own calculations based on HCSO data for 2010. Average rank Pest Gyor-Moson-Sopronborsod-Abaúj-Zemplénbács-Kiskunfejér Hajdú-Biharcsongrádbaranya Komárom-Esztergomveszprém Szabolcs-Szatmár-Beregjász-Nagykun-Szolnokheveszalasomogybékés Vastolnanógrád 1
The National Innovation Office RDI Observatory's own calculations based on HCSO data for 2010. Average rank 2. 2 2. 4 2. 7 3. 9 4. 8 4. 8 0123456 Central Transdanubia Southern Great Plain Northern Great
the regional influence (sectors display similar distribution patterns), or the sectoral influence (regionality does not have a major influence on the geographic distribution of companies).
The correlation calculation is used a procedure to determine how close the correlation is between various probability variables (indicators and/or data.
Spearman's rank correlation allows us to compute the coordinated movement of characteristics measured on an ordained (ranked) data scale
(or transformed into such a data scale). In the example we ranked various innovative industries/sectors according to
with the only difference being that the regional calculation is based on regional data. The county by county distribution of companies engaged in the sectors of the national economy such as the manufacturing of computer, electronic and optical products, electrical energy, gas and steam supply and air conditioning, water supply, professional
, scientific and technical activity as well as information communication and financial and insurance activity shows very strong similarities,
zzmanufacture of computer, electronic and optical products zzelectricity, gas, steam and air-conditioning supply zzwater supply, sewerage, waste management and remediation zzprofessional, scientific, technical activity
The tendencies previously noted in respect to counties become even more clearly accentuated in the context of regional rank correlation analysis. In this context, the pharmaceutical industry displays a significantly negative correlation with other industries/sectors;
The National Innovation Office RDI Observatory's own calculations based on HCSO data and map imaging of the former. 22 We defined corporate research units as any
This accounts for the slight discrepancy between our own and HCSO data. 37 3. Innovation potential 23 It must be noted that we do not know
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Central Hungarynorthern Great Plaincentral Transdanubia Southern Great Plainnorthern Hungarywestern Transdanubiasouthern Transdanubia 7. 7 6. 8 5. 2 4. 8 3
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Figure 36: Number of Accredited Innovation Clusters by region, with an indication of how many members they have.
The National Innovation Office RDI Observatory's own calculations based on MAG (Hungarian Economic Development Centre) data and map imaging of the former. 0 20 40 60
KMOP and AIK tenders The following data show the regional distribution of tender amounts awarded under GOP,
We found no big surprises analysing these data, and we again came to the conclusion that Central Hungary stands out among other regions,
The National Innovation Office RDI Observatory's own calculations based on EMIR (European Market Infrastructure Regulation) data and map imaging of the former. 40 4. Re gional
The National Innovation Office RDI Observatory's own calculations based on PKR data and map imaging of the former.
Statistical data of FP7 participants who signed a grant agreement during the period Figure 41:
The National Innovation Office RDI Observatory's own calculations based on E-CORDA data and map imaging of the former. 26 43 4. Re gional distribution of grants
and engaged in research or technology development as a core activity. Public organisation: any legal entity thus defined by national laws, or international organisation.
which analyses six RDI-relevant data in three different years before creating a normalised complex index (by comparing it to the maximum value of the dataset.
and comprises quantitative and qualitative data at the same time. zzrdi Infrastructure complex index: this index provides a clear indication of the availability of the material and nonmaterial infrastructural resources needed for any kind of RDI activity.
In the table of basic data provided in Appendix 1 we made it clear which indicator is classed under which complex index,
(i e. data of that region whichever scored the highest value in the indicator in question), in other words the maximum value serves as a benchmark.
All these data are indicative of very large disparities between the country's various regions. It is common knowledge that the unemployment data for different regions can vary greatly,
and the number of unemployed graduates in different counties cannot be explained conclusively either by the size
internet subscription prorated to 1, 000 people, 2010 2 405 378 358 312 312 300 289 Appendices 49 Appendices 2. Development in the headcount of researchers employed by individual sectors
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 0 200 400 600 800 1 000 1 200 2000
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 0 100 200 300 400 500 600 2000 2001 2002
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 50 Appendices0 100 200 300 400 500 600 700 2000
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 0 100 200 300 400 500 600 2000 2001 2002
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 0 100 200 300 400 500 600 700 800 900
National Innovation Office RDI Observatory's own calculations based on Eurostat data. 51 Appendices 2000 2001 2002 2003 2004 2005 2006 2007
National Innovation Office RDI Observatory's own calculations based on Eurostat data. Unemployed graduates, capita (left axis) Unemployed non-graduates, capita (left axis) The proportion of graduates within total unemployment,%(right axis) 14.7%11.6%8
The National Innovation Office RDI Observatory's own calculations based on HCSO data. 3. Geographic distribution of unemployment according to qualifications 52 Appendices Unemployed graduates, capita
The National Innovation Office RDI Observatory's own calculations based on HCSO data. Table 1: Rank correlation matrix;
Data source: HCSO) We highlighted strong correlations (above 0. 7) in green. CF Manufacture of pharmaceuticals;
CI Manufacture of computer, electronic and optical products; CL Manufacture of transport equipment; CJ Manufacture of electrical equipment;
Data source: HCSO) We highlighted strong positive correlations (above 0. 7) in green, and negative correlations in red.
CI Manufacture of computer, electronic and optical products; CL Manufacture of transport equipment; CJ Manufacture of electrical equipment;
CI Manufacture of computer, electronic and optical products; CL Manufacture of transport equipment; CJ Manufacture of electrical equipment;
and any data and indicators published therein, can be downloaded from the Kaleidoszkóp website: http://www. kaleidoszkop. nih. gov. hu/54 References Borsi, Balázs Mikita, József (2013:
Centres and peripheries regions in the context of European research and development (Centrumok és perifériák régiók az európai kutatás-fejlesztésben.
Common Research Data warehouse, https://webgate. ec. europa. eu/e-corda/Educational Authority (2013: National competence assessment, 2012 (Oktatási Hivatal, Országos kompetenciamérés) European commission (2013:
id=1410&obj id=4470&dt code=EV N&lang=en Date of download: 17,may 2013 Eurostat Statistical Database: http://epp. eurostat. ec. europa. eu/portal/page/portal/eurostat/home European commission (2012:
Regional Innovation Scoreboard. http://ec. europa. eu/enterprise/policies/innovation/files/ris-2012 en. pdf Date of download:
20,march 2013 GEOX Kft (2013: http://www. geox. hu/Haggett, Peter (2006: Geography global synthesis (Geográfia globális szintézis.
HCSO Dissemination database: http://www. ksh. hu/HCSO (2012: Research and development 2011, Budapest HCSO (2013: Census (2011) http://www. ksh. hu/nepszamlalas/?
+36 (06 1) 484 2500 Central fax number:++36 1 318 7998 E-mail: info@nih. gov. hu www. nih. gov. hu 56 Kaleidoszkóp Kaleidoszkóp (the name refers to the multifaceted nature of RDI) is the name of the information system used by the National Innovation Office.
Kaleidoszkóp's objective is to create an integrated RDI database of the relevant institutions and companies of the sector,
as well as data and analyses supporting RDI policy related decision-making. With the help of this database, RDI stakeholders can be involved in diagnosing problems as may exist within the sector
and work out possible solutions. All Kaleidoszkóp system data and service functionalities are meant to assist public sector institutions
and other organisations in their networking, strategy development and market analysis efforts. Kaleidoszkóp's main objectives:
zzpromote networking within the RDI sector zzassist facts-based decision-making zzassist national and international statistical activity zzprovide solid foundations for RDI strategy-making Kaleidoszkóp's services:
zzgeneric and specific sectoral RDI analyses and statistics zzquality data sources informing analysis zzinformation on public funded RDI projects zzregister of Hungarian research infrastructure facilities
zzmap-based search engine of RDI organisations and businesses zzfinding project partners and mapping project opportunities Kaleidoszkóp is operated by the National Innovation Office RDI Observatory Department.
www. kaleidoszkop. nih. gov. hu Phone:++36 1 484 2500 Fax:++36 1 318 7998 E-mail:
info@nih. gov. hu Web: www. nih. gov. hu kaleidoszkop. nih. gov. hu ISSN 2063-7748 ISBN 978-963-89792-3-0 NATIONAL INNOVATION OFFICE INFORMATION SYSTEM
EUROPEAN COMMISSION Brussels, 27.10.2011 C (2011) 7579 final COMMISSION RECOMMENDATION of 27.10.2011 on the digitisation and online accessibility of cultural material and digital preservation EN 1 EN COMMISSION RECOMMENDATION of 27.10.2011 on the digitisation
and online accessibility of cultural material and digital preservation THE EUROPEAN COMMISSION, Having regard to the Treaty on the Functioning of the European union,
and in particular Article 292 thereof, Whereas:(1) The Digital Agenda for Europe seeks to optimise the benefits of information technologies for economic growth, job creation and the quality of life of European citizens,
as part of the Europe 2020 strategy. The digitisation and preservation of Europe's cultural memory which includes print (books, journals, newspapers), photographs, museum objects, archival documents, sound and audiovisual material,
monuments and archaeological sites (hereinafter‘cultural material')is one of the key areas tackled by the Digital Agenda.
2) The EU's strategy for digitisation and preservation builds on the work done over the last few years in the digital libraries initiative.
The European actions in this area, including the development of Europeana, Europe's digital library archive and museum were supported by the European parliament and the Council, most recently in a Parliament resolution of 5 may 2010 and the Council Conclusions of 10 may 2010.
The Workplan for Culture 2011-2014 established by the Council at its meeting of 18 and 19 november 2010, highlights the need for a coordinated effort in the area of digitisation.
3) On 28 august 2006, the Commission issued a Recommendation to the Member States with a view to optimising, by means of the internet, the economic and cultural potential of Europe's cultural heritage.
The Member States'reports on the implementation of the Recommendation of 2008 and 2010 show that progress has been made.
4) Moreover the context for digitisation efforts and for collaboration at European level has changed considerably over the last few years.
'Europe needs to act now to reap the benefits of digitisation and digital preservation. If Member States do not step up their investments in this area,
It will give Europe's diverse and multilingual heritage a clear profile on the internet,
and the digitisation of their assets will help Europe's cultural institutions to continue carrying out their mission of giving access to
(8) Digitisation is an important means for ensuring greater access to and use of cultural material.
and would avoid overlap in digitisation. It would also lead to a more secure climate for companies investing in digitisation technologies.
Overviews of current and planned digitisation activities and quantitative targets for digitisation would contribute to achieving those objectives.
9) The cost of digitising the whole of Europe's cultural heritage is high and cannot be covered by public funding alone.
Private sector sponsoring of digitisation or partnerships between the public and private sectors can involve private entities in digitisation efforts
and should be encouraged further. In order to be balanced fair and, these partnerships should comply with a number of key principles.
and are being used to co-fund digitisation activities as part of projects having an impact on the regional economy.
Mass digitisation processes can gain in efficiency due to scale. Therefore, the efficient use of digitisation capacity and, where possible, the sharing of digitisation equipment between cultural institutions and countries should be encouraged.
11) Only part of the material held by libraries, archives and museums is in the public domain,
and implemented to ensure a harmonised approach to the issue of orphan works throughout the EU. For the largescale digitisation of out-of-commerce works,
which resulted in a Memorandum of Understanding signed in Brussels on 20 september 2011 should be seen as a model for further dialogues to facilitate agreements for the digitisation of as much of the out-ofcommerce material as possible.
Rights information databases connected at European level can bring down transaction costs for rights clearance. Such mechanisms should
will make the site more interesting for the users, and should therefore be encouraged. The overall target of 30 million objects by 2015 is in line with Europeana's strategic plan,
as determined and selected by the Member States) through Europeana will enrich the content of the site, in line with the expectations of the users.
when the hardware and software used to store them becomes obsolete, material may be lost when storage devices deteriorate over time,
Web-harvesting is a new technique for collecting material from the internet for preservation purposes.
Digitisation: organisation and funding 1. further develop their planning and monitoring of the digitisation of books, journals, newspapers, photographs, museum objects, archival documents, sound and audiovisual material, monuments and archaeological sites
(hereinafter‘cultural material')by:(a) setting clear quantitative targets for the digitisation of cultural material, in line with the overall targets mentioned under point 7, indicating the expected increase in digitised material
which could form part of Europeana, and the budgets allocated by public authorities, (b) creating overviews of digitised cultural material
and the private sector in order to create new ways of funding digitisation of cultural material and to stimulate innovative uses of the material,
while ensuring that public private partnerships for digitisation are balanced fair and, and in line with the conditions indicated in the Annex;
EN 5 EN 3. make use of the EU's Structural Funds, where possible, to co-finance digitisation activities in the framework of regional innovation strategies for smart specialisation;
4. consider ways to optimise the use of digitisation capacity and achieve economies of scale, which may imply the pooling of digitisation efforts by cultural institutions and cross-border collaboration, building on competence centres for digitisation in Europe;
Digitisation and online accessibility of public domain material 5. improve access to and use of digitised cultural material that is in the public domain by:(
a) ensuring that material in the public domain remains in the public domain after digitisation, (b) promoting the widest possible access to digitised public domain material as well as the widest possible reuse of the material for noncommercial and commercial purposes,
(c) taking measures to limit the use of intrusive watermarks or other visual protection measures that reduce the usability of the digitised public domain material;
Digitisation and online accessibility of in-copyright material 6. improve conditions for the digitisation and online accessibility of in-copyright material by:(
and agreed by stakeholders for the large scale digitisation and crossborder accessibility of works that are out-of-commerce,
and promoting the availability of databases with rights information, connected at the European level, such as ARROW;
EN 6 EN (b) making all public funding for future digitisation projects conditional on the accessibility of the digitised material through Europeana,
(e) ensuring the use of common digitisation standards defined by Europeana in collaboration with the cultural institutions
in collaboration with the cultural institutions contributing content to the site; Digital preservation 8. reinforce national strategies for the long-term preservation of digital material,
(c) allowing the preservation of web-content by mandated institutions using techniques for collecting material from the Internet such as web harvesting,
I Public-private partnerships for digitisation In order to make rapid progress on the digitisation of our cultural heritage,
public funding for digitisation needs to be complemented by private investment. Therefore, the Commission encourages public-private partnerships for the digitisation of cultural material.
It calls on the Member States to stimulate such partnerships which should comply with the following key principles:
1) Respect for intellectual property rights Public-private partnerships for the digitisation of collections in cultural institutions should fully respect the European union
Agreements should be fully compliant with EU competition rules. 3) Transparency of the process Agreements for the digitisation of collections held by cultural institutions should be awarded after an open competition between potential private partners. 4) Transparency of agreements
and private partners for the digitisation of cultural collections should be made public. 5) Accessibility through Europeana The conclusion of a public-private partnership should be conditional on the accessibility of the digitised material through Europeana. 6) Key
The envisaged digitisation quality, and the quality of the files that will be given to the cultural institutions.
The time-scale of the digitisation project. EN 10 EN ANNEX II Indicative targets for minimum content contribution to Europeana per Member State Number of objects in Europeana per MS*Indicative Target 2015**AUSTRIA 282
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