ICT-Vienna Media Works Set

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    @neurist - die Verlinkung IT und Medizin

    Michela Perathoner

    Ein Besuch in der Abteilung fr scientific computing der Uni Wien um zu erfahren, was

    wissenschaftliches Rechnen eigentlich ist, wozu es gut sein soll und was in der Forschung damitalles bewirkt werden kann.

    Es ist, als ob wir die maximale Geschwindigkeit des schnellsten Autos alle 18 Monate verdoppelnwrden- es mag wohl wie ein banales Bespiel klingen, aber fr Nicht-Informatiker ist das Beispielleicht verstndlich: Wilfried Gansterer, Vorstand des Forschungslabors ComputationalTechnologies and Applications der Universitt Wien, trifft den Punkt, wenn er begeistert von derstndig wachsenden Leistung der Computer-Prozessoren spricht. Der Vergleich, der Autoindustrieentnommen, vereinfacht nmlich nicht IT-Experten um einiges die Vorstellung. Laut demsogenannten Mooreschen Gesetz, nach Gordon Moore benannt, verdoppelt sich die Anzahl derTransistoren auf einem handelsblichen Prozessor alle achtzehn Monate. Das heit, dass die

    Computer-Leistungen stndig zunehmen, Jahr fr Jahr. Sollte ja an sich keinen verwundern: wererinnert sich nicht an den Commodore 64 der Neunziger Jahre? Die aktuellen Laptops wren vorzwanzig Jahren sogenannte Supercomputer gewesen, erklrt diesbezglich Siegfried Benkner,Vorstand der Abteilung fr wissenschaftliches Rechnen der Universitt Wien.Aber es ist nicht nur von Supercomputern die Rede, wenn man in den Rumlichkeiten derAbteilung fr scientific computingder Fakultt fr Computerwissenschaften in Wien herumstbert.Cloud computing und Grid sind ebenso Fachbegriffe im wissenschaftlichen Rechnen, einerinterdisziplinren Forschungsdisziplin, die durch numerische Simulation neben den beidenklassischen Sulen der Forschung, Theorie und Experiment, hinzutritt. Und in vielen Natur- undIngenieurwissenschaften Kosten verringert und Berechnungen und Darstellungen ermglicht, diereal gar nicht durchfhrbar wren. Konkret kann es sich dabei um Unfallssimulationen ebenso wieum Wettervorhersagen oder chirurgische Eingriffe handeln: die Anwendungsbereiche reichen vonder Autoindustrie bis zur Molekularbiologie. Denken wir doch an eine Gehirnoperation, erklrtPeter Brezany, Professor der Abteilung frscientific computingin Wien, und an die Tatsache, dassein Tumor beim ffnen des Gehirnschdels einem unterschiedlichen Druck ausgesetzt wird undsich dadurch verschieben kann: Computersimulationen knnen dies vorhersehen und darstellen.Medizinisch natrlich ein ganz schner Vorteil.Aber wenn man von scientific computing, Englisch fr wissenschaftliches Rechnen, spricht, gehtes nicht nur um Auto-Design, graphischen Output, Simulationen oder schnelles Rechnen:Datenspeicherung und virtuelle Verbindung zwischen Firmen, Krankenhusern oder Labors zhlenebenso zu den Forschungsbereichen der Abteilung der Uni Wien. Wie im Falle des Projekts

    @neurist, von der Europischen Kommission im Rahmen des FP7 finanziert: 17, 5 Millionen Euro,ungefhr 13 davon von der EU beigesteuert, um zwischen 2006 und 2009 gemeinsam mit 28Partnern eine allgemeine Grid-Infrastruktur zur Verwaltung und Verarbeitung heterogener Daten zuentwickeln. Worum es bei diesen Daten geht? Wie der Name des Projekts, das mittlerweile demEnde zusteuert, verrt, um Aneurysmen.Was das sind, wei man sptestens seit populre Krankenhausserien wchentlich von dem einenoder anderen Fall berichten. Medizinisch handelt sich dabei um Ausbuchtungen beziehungsweiseAusweitungen von Arterien, die beeren- oder sackfrmig, kahnfrmig, geschlngelt oderrankenfrmig aussehen, und an Stellen entstehen, an denen die Gefwand geschwcht ist und nichtber eine normale Muskelschicht verfgt. Ursachen dafr knnen eine angeborene Schwcheebenso wie eine durch Verletzungen erworbene Vernderung in den Gefwnden sein. Ein

    Skiunfall, zum Beispiel. Was aber die Informatik, beziehungsweise das wissenschaftliche Rechnen,damit zu tun haben sollen? Technisch spricht man von der Schaffung einer GridInfrastruktur bereinen gesicherten Webservice. @neurist sieht nmlich, auf fnf verschiedenen Teilprojekten

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    unterteilt, die Erstellung einer Datenbank vor, die ermglicht, dass die Informationen der einzelnenPatienten zwar in den eigenen Krankenhusern bleiben, aber virtuell auch anderen rzten zurVerfgung stehen.Die Privatsphre wird dabei geschtzt, und die Patienten der fnf Krankenhuser, die bisher amProjekt teilgenommen haben (Genf, Oxford, Rotterdam, Barcelona, Sheffield), wurden nach Ihrer

    Einwilligung gefragt. 783 Frauen und 420 Mnner haben bisher zugestimmt. Der Zugriff aufDaten von Patienten verschiedener Krankenhuser in unterschiedlichen Lndern ermglicht zumeinen die Vergleichbarkeit von Aneurysmen und vereinfacht somit die Entscheidungen von rzten

    bezglich eventueller Eingriffe und Behandlungen ebenso wie die Berechnung von Risiken meintMartin Khler, Forscher der Abteilung frscientific computingder Universitt Wien. Ein weitererVorteil betrifft die Forschung: Der Zugriff auf verschiedene Daten und Beispiele ermglicht es,Links zur Genetik herzustellen.Klingt wohl einfacher, als es ist, denn verschiedene Datenbanken im medizinischen Bereichmiteinander zu verbinden, um eine Art Netzwerk von Krankenhusern und Forschungslabors zuschaffen, bentigt viel computing power, um die Daten zu verwalten und zu analysieren. WeitereSchwierigkeit beim Ganzen sind erstmals der Datenschutz: Gesichter mussten natrlich

    herausgeschnitten werden, damit die Patienten nicht erkannt werden knnen, meint dazu MartinKhler, und die Daten befinden sich ja dank des Systems im eigenen Krankenhaus und werdennicht in einen anderen database kopiert.Dann natrlich auch noch die Kommunikation zwischen Informatikern und rzten: um graphischeDarstellungen, Simulationen und Datenspeicherungen zu ermglichen, muss man sich nmlicherstmals zusammensetzen. Computer-Wissenschaftler knnten zwar ein System erarbeiten, aberkein Arzt wre dann in der Lage, es zu verwenden, meint Siegfried Benkner. Was die Informatik-Forscher der Uni Wien vor Beginn des Projekts ber Aneurysmen wussten? Kaum was, wieGerhard Engelbrecht, Mitarbeiter am Projekt, lachend erzhlt. Zwar hat er im Laufe der Monateimmer mehr darber erfahren, aber Medizin und IT sind natrlich zwei separate Dinge. DasSystem schafft ja nichts allein, sondern stellt rzten nur die Daten und Darstellungen zurVerfgung, erklrt Martin Khler. Aber es sei natrlich wichtig, Experten miteinzubeziehen, diesowohl mit Computern als auch mit den Informationen etwas anfangen knnen. Insgesamt sind amProjekt ungefhr 100 Personen beteiligt, mindestens zwei Drittel davon sind rzte.Was in Zukunft kommen soll? Das Projekt soll natrlich nicht mit dem Abschlussdatum zu Endegehen: die Struktur wre schon mal geschafft, und neue Daten und Informationen werden stndighinzugefgt. Und eine Erweiterung des Netzwerks und somit der Teilnehmer wrde natrlich nochmehr Mglichkeiten mit sich bringen.

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    Providing Instruments for Data Surgery

    Viktorija Rusinaite

    Supercomputers and grid computing resources provided for @neurist project helps researchers in

    the medical field to cut into the vast amount of data and extract the knowledge about diagnosis andtreatment of the cerebrial aneurysm.

    What do you do with your old supercomputers, are they recycled?, asks one of the participantsof the MyScience ICT workshop in the University of Vienna. Oh, I keep my flowers on the lastone, its in my office, Prof. Siegfried Benkner answers with a joyful smile.Later on he will actually take all of 15 students from all over Europe to his office to show this hugefridge-like iron baby, that he is so proud of. This non working rarity and collectable item nowserves as a shelf for flowers and was last seen working before unfortunate overwatering few yearsago. Along with the flowers, its probably the only one trifle in the all-functional office.Super computers are actually huge machines designed to perform tasks requiring lots of

    computational resources, such as memory, processing capabilities. The capabilities of our ownpersonal computers or netbooks are more or less the same as the capabilities of super computersused 20 years ago. Some of the new and working ones are used, explored and exploited for the sakeof science, this is also the case in University of Vienna, department of Scientific Computing.Supercomputers among many different resources are used in interdisciplinary projects involving

    both medical and IT researchers and practitioners to improve medical research conditions. Suchinterdisciplinary project called @neurist aimed at treating aneurisms since 2006 is collectivelycarried out by the department and 32 other partners from hospitals and research institutes all overEurope.

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    Improvements in software and hardware and its uses in projects aimed at improvement of medicaltreatmens are among the main reasons why this cold friday afternoon in Vienna I knock on theoffice door of Head of Department of Scientific Computing, professor Siegfried Benkner.@neurist project is aimed to improve diagnosis and treatment of cerebral aneurysms, a small bloodfilled dilations usually occurring in arteries or aorta near human brain and resulting severe bleeding

    on brain and sometimes even death. Treatment of these dilations are usually either endovascular orinvasive surgery, which both are costly and does not prevent the recurrence of aneurysm, becauseaneurysms occur as the symptom of other diseases.For a long time treatments of aneurysms were not personalized and rather based on doctorsexperience and generic guidelines. The diagnosis was based on size and location of the dilation,which was derived from medical imaging and risk factors such as age, sex and etc. There weresome evidences that there may also be genetical reasons for the natural history and evolvement ofaneurysm, but the possibilities of exploration and comparative analysis were limited because oflarge amounts of data, which are difficult to manage and analyze. Thats how @neurist projectuniting research labs, hospitals and IT specialists came into spotlight of FP7 programme, funded byEU.

    @neurist project is distinctively interdisciplinary project, says prof. Benkner, who is leading oneof IT resource provider groups in @neurist. Some of the partners in the project are hospitalscollecting all relevant data with the aim to collect data samples from 1200 patients, others search forthe evolvement patterns in the data collected, medical solutions for the problems. To make all ofthis happen a lot of computational power is required in order to deal with a large amounts of patientdata collected in the hospitals, so @neurist is based on technology called grid computing. Gridcomputing is about connecting computer resources, computers, databases, the instruments over theinternet in order to provide a platform for scientific computing, applications, simulations and so on.You can use all distributed computers as one big virtual computer, explains prof. BenknerAs databases and computers of @neurist project are based in different Western European countriesas well as different scientists using the system, the kind of service is required. The end-users of theservice would submit the query into the system and thanks to the virtualisation software anddistribution systems wouldnt even notice which computer and where performed their task.With the help of this huge system and relevant data collected you can for example simulate themovement of the aneurysm inside the skull of the patient, which would be caused by invasivesurgery. Therefore the surgeon can plan where to cut in when performing the surgery.One of the problems we face in modern medicine is fragmentation of data, acknowledges

    professor Benkner, that means that each hospital has its own data formats and different databases.In order to analyze large amounts of data, group it and extract the knowledge from it the unifiedformat is needed. Thats when ontologies comes into picture. By having ontology we can say that in

    one hospital it is called X and in other it is called Y, but it is in fact the same type of informationand then we can combine it technically, adds professor Benkner. From the computational pointof view the language or nationality of the data does not matter, because in this respect DNA, or thequalities of blood sample are discrete, even if presented in different data formats they can be unifiedwith the help of ontology. Thats why medical scientists in the project then can track diagnosticsimilarities in different cases and foresee the evolvement of the disease and suggest the treatment.Moreover the same system adapted to the end user could be used in other fields of research or

    business.

    The most significant innovations are medical, says prof. Benkner, during the project people havegot much better understanding about aneurisms and their treatment.

    www.aneurist.org

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    @neurIST @work

    Hanna Siemaszko

    Dr Gerhard Engelbrecht talks about heroism in programming, the @neurIST project and his work at

    the University of Vienna

    H: Do you consider yourself a hero?G: A hero? Actually no. A hero in research probably, but I see myself more as a contributor tofurther development. I like doing my job, of course. But a hero for me is someone who reallyinvents something spectacular or earth-shaking.H: Professor Benkner mentioned that there is a need for hero programmers.G: Hes surely right. But a hero programmer in my eyes is something different. You have to beopen to new frameworks, new techniques, new style of working. Hes a professor teaching softwaredevelopment. He teaches what we executed earlier. There is a new trend called extreme

    programming which means two people are working together on the same problem probably on the

    same computer. They develop together. This was named two-three years ago, but we had made thisearlier. We found out that it is very effective and you progress very fast.H: It means that you get a similar task and you are trying to find out different solutions andcompare?G: No, youre working on the same problem. One is typing, the other one is watching and then youchange. This really happens very fast because you immediately see the problems or possible errorsthe other one makes. And then you can correct them immediately. Four eyes see more than two.H: Was it used for @neurIST as well?G: Sure. When we develop things, we usually have to do something from scratch very fast. Thismeans getting a prototype in a couple of hours. Being that effective if you are alone is very hard

    because you are often stuck with a problem and you iterate it over and over. If you do this with twoor even three people you usually get a result very fast.H: What is the outcome of @neurIST for the University of Vienna and your department? What didyou gain?G: We learnt a lot about fields we were not used to. Medicine, aneurysms, life science area.H: You know more about red snowmen?G: [laughs] Aneurysms do look like red snowmen. Who knows what they would resemble if youcoloured them blue. We gained new software and worked a lot on data integration which wasrelatively new to our department. We dealt with huge data sets, integrating them and making themaccessible via the Internet. Also in the area of security, new techniques, new frameworks. Therehave been many developments we can now apply in other systems. Of course in the cloud

    computing area we made some progress, also with Amazon and Google cloud computing. We hadno experience in this when the project started.H: Both grid computing and cloud computing were used in the project?G: Originally we said we just want to have a cyber infrastructure, kind of an umbrella covering allthose areas. We were experienced with grid computing which means we had frameworks, butmainly in the area of high-performance computing and compute-intensive applications. You arealways dealing with huge data sets and some computing is involved. We did it on certain machineswe have here, put it on a server, and put it in a cloud, for example the Amazon cloud. We made

    progress here and we can build on that in our future projects. From our perspective aneurysms arejust one direction you can do research with. The system we made is generic enough to apply toother problem domains.

    H: Would they be medicine-related?G: No. You can go back to pure research like natural sciences, physics, chemistry. They havesimilar problems in the technical sense as they have huge data sets and some simulation or

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    computation is needed. So the basic approach from the IT perspective is the same. And our goal isto apply this system in other problem domains. Not only medicine. But of course medicine is veryinteresting because they have huge datasets and very compute-intensive applications.H: The program you were showing was @neuLINK. I noticed on the leaflet of @neurIST that themain goal was to develop gene identification. You mentioned that this is still under construction.

    Does it mean that the main aim hasnt been reached?G: No. There are many bits and pieces to be put together to make this work. I have shown you theWeb portal. The application at the back is already in place and runs but its not accessible for all the@neurIST people. There were some little problems we have not foreseen, but the researchers whoare concerned with this application are already working with it. Actually we have reached the goal,

    but we have not integrated it into the portal yet. I have not shown this because currently its hard topresent. No pictures, so to say.H: The @neurIST project should finish this month.G: We have an extension until the end of March 2010 when the final review is. But some partnersare closing the project now. As we are providers of certain services we will be involved until thevery end. There are actually plans to make at least some demonstrators available for a longer period

    of time. I think the services we have developed (along with the Web portal) will run at least for thenext full year. We also plan to make a software package which you can sell or rather give to other

    people. For example some South American countries wanted to build a similar system basing on it.H: So it means commercialising it.G: Probably not immediately. There are more clinical centres which have expressed interest in

    participating and in contributing. There are already plans to keep this up and running and evenextend it. Which means our collaborators will contact us for support and this will continue. I thinkthe system will stay open with no commercial interest. On the other hand, there is the idea ofcreating a software package and some companies which are involved in the project are surelyinterested in commercialising at least bits of it. For example in the area of data security. Because thesecurity system is very complex and there were many developments in securing each data transferand also making a role-based access system. This can be put out of the system and exploitedseparately and I think this will surely be done. I would say that at least some bits of it will becommercialised within the next 1-2 years.H: Do you know exactly in which field?G: I think there is interest in applying it in financial transfer systems. Especially in the UK. There isalready a prototype prepared for the HSBC bank. They have expressed huge interest. The softwareis currently released as open source, but as it is with such products usually no support leads to themending up dead somewhere on the Internet.H: You have also personally gained from the project because your PhD thesis is related to what youwere doing. I assume there were numerous times when you had to explain your area of research to

    the general public.G: My personal contribution to this was in the area of making guarantees possible. Which meansthat if you have a certain computationally-intensive task, for example CT imagery construction, thishas to be finished in certain time. You can say in advance, ok I put you into the CT scanner and 50minutes later you will have the full image. This is basically what I do. This is called Quality ofService and I build systems around it and make research related to it.H: Quality of Service which means that you provide services in a G: way that you can do those guarantees. This is even more interesting if you have a situationwhere during a surgery some computation is required. Because then you have to do some resourcereservation in advance so that you know that the computational resources are available during thesurgery. This was basically my contribution.

    H: The project is about to finish. Is there anyone of your collaborators writing new projects to applyfor the EU funds? I noticed you are not participating in the new project of your Faculty that isstarting in January 2010. [PEPPHER]

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    G:Thats true. There are activities of some of the @neurIST members in the consortium. They wantto have a wider approach in the area of general data integration and I think our Institute will

    participate in this as well. The proposal is planned for March or April next year and if everythinggoes well the project will have presumably started by the end of next year. We are also thinkingabout using the software we have and all the partners and their experience to go to an even higher

    level to have a general data integration system for medical patient data.H: Dealing with different diseases and not a particular one?G: Yes.H: Your colleagues will be medical specialists afterwards.G: I presumably will not participate in this, but I think others: Alexander Whrer and probablyMartin Khler will. They will gain even more experience in the medical field.

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    Una giovane Europa comunica la scienza

    Viviana Lupi

    Steven Afonso Portela ha 22 anni e arriva dal Portogallo. Il suo progetto per il 2010 fondare una

    rivista di scienza dedicata ai bambini fino ai 12 anni.Veronica Frigeni di anni ne ha 21 e arriva dallItalia. E giornalista freelance e vuole comunicare lascienza a un pubblico di non esperti: Con i miei articoli, dice, cerco di rendere gli argomentifacilmente comprensibili, ma non lesino in quanto a provocazioni. Comunicare non mai a sensounico, provo a innestare un dibattito, a coinvolgere il pubblico.Hanna Siemaszko, 24 anni dalla Polonia, giornalista, traduttrice e insegnante. La mia missione,afferma parlando dei suoi tre lavori, trasferire una cultura nellaltra e aiutare le persone a capire.Sono alcuni dei giovani giornalisti scientifici che hanno deciso di partecipare al progetto MyScience, finanziato dallUnione europea e coordinato dallEURAC di Bolzano, sotto laresponsabilit di Farah Fahim, con la collaborazione dellassociazione giornalistica Polis (Polonia)e della societ di comunicazione Eurideas (Ungheria).

    Grazie al progetto, 90 giornalisti scientifici parteciperanno a sei differenti workshop a Vienna,Gdll (Ungheria), Praga e Bolzano, per conoscere da vicino il lavoro degli scienziati in alcunisettori chiave della ricerca europea: cellule staminali, tecnologie dellinformazione e dellacomunicazione, energie rinnovabili, ambiente, scienze umanistiche e tecnologie chimiche.Il primo workshop si svolto con successo allUniversit di Vienna dal 7 all 11 dicembre, gli altrisi susseguiranno fino al 13 marzo, mentre il 28 maggio prevista la conferenza finale a Bolzano (Lasede potrebbe essere Bruxelles al posto di Bolzano ).A Vienna, 15 giornalisti, provenienti da Croazia, Estonia, Francia, Italia, Lituania, Polonia,Portogallo, Romania e Slovacchia, sono stati ospitati dal Dipartimento di Scientific Computingdiretto da Siegfried Benkner e hanno potuto approfondire le tematiche pi attuali nel campo delletecnologie dellinformazione, come la diffusione dei super computer nel mondo e le caratteristichedellInternet del futuro, nonch gli aspetti etici legati ad esempio alla protezione dei dati personali.In particolare, i ricercatori hanno presentato ai partecipanti tre progetti finanziati nellambito delSettimo Programma Quadro dellUnione europea: @neurIST, ADMIRE e PEPPHER, volti asviluppare rispettivamente nuove tecnologie per gestire i dati medici sugli aneurismi cerebrali,estrarre con maggiore efficienza informazioni dai grandi data base e realizzare computer conelevate velocit di calcolo.Unesperienza di cui i giovani giornalisti faranno tesoro nella pratica quotidiana di comunicare lascienza. Finalit, questa, che sembrano voler interpretare con tenacia. La mia rivista di scienza per

    bambini, specifica Steven Afonso Portela, coster uno o due euro. Mi occuper di tutto, anche

    dellimpaginazione. Il mio obiettivo che i portoghesi familiarizzino con la scienza.Auspicio senzaltro valido e non solo per il popolo portoghese.

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    Advanced Data Mining and Integration Research for Europe

    Samuel Krolk

    All over the world, the amount and the complexity of data is doubling each year. For last few

    decades, computer performance was used mostly for modeling and simulation. However in present,there is a strong need to approach the existing data in such a way, so we can extract a value. Enterdata mining.

    Data miningIs data mining the same thing as statistics? we asked professor Peter Brezany from University ofVienna. Statistics is used mainly for analyzing existing data. Data mining focuses on finding

    patterns in data. In some way, data mining uses statistics as one of its tools. In last few years, datamining is becoming a necessity. From definition, data mining refers to identifying valid and

    potentially useful patterns in large volumes of complex data. These patterns can be useful for eitherprediction or description. The end product of data mining is knowledge.

    Why do we need data miningJust think about this: Every our move in a modern world is associated with a collection of data.Since approximately 2007, it is not possible to persistently store the amount of data that is collectedevery day. In 2009, 40.1018 bytes of data will be generated. said Peter Brezany on the account ofdata management. Management of data is quite different in commercial and science fields.Commercial data are not so complex and they have a certain value for the companies involved.However scientific data is much more complex and we usually need a high performance computingto analyze them. Despite the fact that we need a lot of resources for a scientific research, the benefitfor the society, most of the time, cant be seen immediately.

    Data mining methodsData mining specialists use many methods while theyre mining data for knowledge or valuableinformation. One of the simplest and widely used methods is called Association Analysis orAssociation rule learning. In a common language, we can say that this method is looking forassociations between relevant variables. Best use case is the supermarket, where people who boughtcertain type of product also wanted to buy another product, which is somehow associated with thefirst one. Or from the other point of view, people from the age range 20 to 30 and with a certainlevel of education, were interested in certain portfolio of products. Or we can also identify, which

    products are often bought together. This is why this method was at the time also called marketbasket analysis. You can probably see that this leads us directly towards the targeted marketing,

    which is a visible outcome of data mining for us (end users).Other interesting method is classification. It basically does what it says. Classification tries toarrange the data into groups. To achieve this, classification can use many complex algorithms,ranging from Decision Tree Learning to Neural networks. You probably heard a term Clustering.This is almost the same thing as classification, except the fact, that groups are not pre-defined, theyare created at runtime.

    Interesting facts about project ADMIREData mining is a complex topic already, but there is one more issue we have to cope with. Sourcesof data are usually distributed and heterogeneous. Users and developers which do data mining andintegration strongly need an abstract view over the whole lifecycle of data. Aim of the ADMIRE

    project is to provide this kind of view and in addition also a powerful framework and tools toapproach such a large system.

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    The ADMIRE project is funded by EU and its total budget is 4,3 Million EUR. Participatinguniversities are from UK, Austria and Spain. Work on ADMIRE project is divided into six work

    packages, ranging from high-level model and language research, through architecture to datamining tools development.

    Real world applicationsAs a proof of concept (aim of work package six), ADMIRE framework is deployed at two places sofar. These are only testbeds for ADMIRE framework, which is abstract in its nature and can beapplied to many other areas and types of problems.

    Flood modeling and simulationFirst real world usage of ADMIRE framework takes place in Slovakia at Slovak Academy ofSciences. Areas near major rivers in Slovakia are under the certain risk of flood. To build a reliableenvironmental model for simulations, there is a need to collect huge amount of heterogeneous datafrom many meteorological and hydrological stations and also other domains. explains dr. IvanJaniak, who works for ADMIRE project in University of Vienna. There are existing physical and

    mathematical environmental models which are used today to make predictions. However, the floodprediction is very complex problem, which needs a lot of accurate input data to make an accurateprediction. There are many challenges. For example when we talk about integration of data, thereare different time steps, grid size and so on.

    The factors affecting water content in soils

    Customer relationship analytical platform

    This place of deployment is in Poland and serves for a commercial company called Comarch. Theyneed to perform an advanced business analysis such as customer segmentation or churn prediction.Churn prediction allows companies to foresee reasons why a customer might stop using their

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    services or products, so they can make better decisions to prevent it. ADMIRE testbed at this sitealso allows users to create reports and analysis.

    Ethical issuesTools cant be dangerous, only people can be dangerous. Scientists are only developing tools,

    said Sabri Pllana as a reply for a doubtful comment from the group of journalists. This is certainlytrue in many domains and environments, and it is especially true in computer science. The issue ofsecurity of sensitive data in computer networks and storage systems can be on a very high level. Butin the end, there is only human that is going to operate a computer and human can do harm,regardless if the data is on paper, which is locked in a locker, or stored in a remote database. Thusthis discussion has no place in scientific discovery and should not be slowing down the progress incomputer science. When scientific research will make an output, which can be implemented andused in a real word and to serve people, only after that, we can open a discussion about informationsecurity and moral aspects.

    Article was made with a kind support of My Science organization and the department of Scientific

    Computing on University of Vienna.

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    L'uomo oltre il dato

    Veronica Frigeni

    Questioni prospettiche e di valore: con @neurist il paziente diventa il dato, e il dato possibilit di

    salvezza. Integrazione, analisi, calcolo del rischio e simulazione scandiscono la via informatica allalotta contro l'aneurisma cerebrale.

    Nome, et, professione.Talora interessi, peculiarit estetiche, e perch no fede politica.Descrivere una persona, sceverarne specificit e unicit, si risolve molto spesso in un fumosocollage di dati lontani e irrelati, magari mutevoli o incompleti, certo egualmente importanti. Dati,appunto. Frammenti di identit, di persone. Nuovi oggetti del sapere.Secoli fa la scienza era paradigma empirico, fatica sporca, frutto di estenuanti osservazioni emeticolosi resoconti in collettori di analogie e varianti; con la modernit germogliano brillantispeculazioni, astrazioni, modelli; negli ultimi decenni emergono infine soverchianti simulazione e

    data mining.Terminale di questa evoluzione storica, il progetto @neurist inanella tali modi operandi:osservazione, confronto, integrazione, simulazione, e l'intento di costruire una certezza, una verit,o forse solo il passo successivo.Tecnicamente esso si basa su una catena di strumenti articolata in cinque livelli d'azione: @neurisk,che calcola il rischio personale combinando i dati del paziente, @neuendo incaricato di computare ildesign ottimale negli strumenti chirurgici, @neulink, ispettore dei legami tra corredo genetico e

    probabilit di contrarre la malattia, @neufuse, simulatore 3D dell'intervento, infine @neucompute/info, responsabili della sicurezza dei dati e dell'accessibilit immediata per l'utente finale (il medico,appunto).Come dire, un aggiornamento in chiave wiki delle antiche tabulae di osservazione, un databasevirtuale, illusorio, che smette di esistere quando si interrompe la connessione tra gli enti

    partecipanti, cosicch i dati non evadano mai dalla loro sorgente ospedaliera, legittimando un flussoprotetto e sempre aggiornato.Un'enciclopedia modulata su casi reali, quotidiani. Sequenze di immagini, statistiche, percentuali, el'opportunit per ogni medico coinvolto di accedervi, confrontare il caso del proprio paziente con glialtri memorizzati, servirsene come riscontro per decidere se l'intervento indicato ed eventualmentein quali modalit, e persino simularlo parametricamente on demand.Capire genesi, evoluzione e rischio di rottura, riconoscerne l'incidenza sul singolo individuo,simulare pressione del bisturi e resistenza cerebrale: insomma, prevenire, guarire, salvare. Poterridurre del 50% trattamenti spesso controproducenti, risparmiando complessivamente centinaia di

    milioni di euro annui.Tutto questo, invero, grazie a dati.Eterogenei in forma (testi, immagini, diagrammi) e contesto (tra linee guida generali e studispecifici sugli aneurismi cerebrali sia in vitro che in vivo, sino alle peculiari manifestazioni delsingolo paziente), misurabili in grandezze incomparabili(dall'atomo all'organismo), ma tra loro

    perfettamente integrabili.Del resto l'intero funzionamento di @neurist si basa sull'intersezione di due direttrici diintegrazione, l'una verticale, relativa esclusivamente ai dati, l'altra orizzontale, istituente una tramadialogica tra ospedali e service provider. Reticoli di infrastrutture distribuite su larga scalarealizzano infatti simultaneamente l'accesso e l'analisi di ingenti quantit di dati che, pur localizzati

    in sedi differenti, consentono persino di rintracciare l'intera storia clinica del paziente.Dati, appunto, e dietro loro uomini. Molteplici e variamente declinati, cos come la percezione, lasintesi di ogni identit.

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    Si proclama che fine ultimo di @neurist salvare vite umane.Ascoltare le parole di Martin Kohler, membro dello staff tecnico del progetto nonch ricercatore neldipartimento di Scientific computing dell' Universit di Vienna , capire se possa essere questa la via

    per creare una sorta di carta d'identit sanitaria valida in ogni meandro d'Europa.

    Cauto e ottimista, la tecnica ormai pronta, la sfida altrove.Da una prospettiva tecnica sicuramente possibile sviluppare un'infrastruttura per una carta diidentit della salute europea, ma sono aperte molte sfide. Gi molto lavoro stato fatto in questadirezione, ma le maggiori criticit sorgono dalla necessit di armonizzare i differenti sistemi legali,dalla priorit di sciogliere nodi etici, nonch dalla necessit di implementare sicurezza dei dati e

    privacy.@neurist ovvia a questo ultimo problema associando i dati di ogni paziente ad una stringaalfanumerica e proibendo la condivisione di immagini in cui si possa poi riconoscere l'uomo.Sinonimi, uomini nascosti, uomini oltre il dato.Eppure una carta di identit della salute digitalizzata proietterebbe un interessante, specularerovesciamento prospettico: la carta in tasca, non pi l'uomo dietro il dato, ma il dato oltre l'uomo.

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    Informatique

    Explorez la flore cache du monde

    Matthieu Dailly

    Tous les ans, 6000 milliard de milliards d'informations (IDC/EMC) sont cres sous forme dedonnes informatiques (0 et 1), trois fois plus que ce qu'il n'a jamais t crit dans les livres (1).Impossible de tout stocker. Les scientifiques tentent d'organiser cette matrice afin d'en utiliserune partie dans leurs recherches. L'Europe a dj investit plusieurs milliards d'euros dans la culturede son jardin numrique .

    De l'tude du plus petit cosystme sur Terre celle des vnements clestes, les scientifiquesutilisent des ordinateurs pour simuler les ractions biochimique et physique ou tout simplement

    prvoir la mto. Leurs expriences font natre une multitude de donnes qu'il faut ensuite trier,traiter, analyser... A l'universit de Vienne (Autriche)(2), des chercheurs tentent de dvelopper la

    prochaine gnration d'outils informatiques qui permettront d'organiser cette masse informe(intgration, bases de donnes, logiciels pour infrastructures massivement parallles, ....)

    Jaguar - Cray, Roadrunner, Kraken XT5, JUGENE - Blue Gene, ces noms barbares sont ceux desnouveaux cerveaux de la science (ils ralisent jusqu' un million de milliards d'oprations laseconde). En climatologie ou en sismologie, les modles informatiques sont corrigs en temps rel

    par une arme de capteurs. C'est le Quatrime Paradigme, prcise le chercheur viennois PeterBrezany, la force des observations historiques couple celle des modlisations informatiques .Au laboratoire Cern, le berceau du Web, ces monstres sont utiliss pour simuler le Big Bang .Tandis que certains tats les utilisent pour recrer les conditions d'un essaie nuclaire (CEA,France).

    Mais ces techniques sont aussi utile au monde industriel. Les simulations sont utilises par lesconstructeurs automobiles et aronautiques pour la conception de prototypes. Plus tonnant, laPlaystation 3 et ses processeurs graphiques (conues pour la 3D, les simulations physiques...), sont,eux, utiliss dans des programmes de lutte contre les maladies dgnratives, le cancer ou encore leSida (Folding@Home, FightAIDS@Home). Les machines sont organises en cluster , reliesentre elles, afin d'accumuler leur puissance. Reste qu'administrer ces infrastructures complexes endevient d'autant plus difficile. D'o l'origine du projet Peppher de l'universit de Vienne. Un

    programme qui tend crer un logiciel assez mallable pour s'adapter aux composants lectroniquesde demain, leur amortissement excdant parfois 20 ans.

    Comme dans tout projet humain, il y a un risque utiliser ces techniques. Mais le potentiel pournotre bien tre tous est formidable, explique Sabri Pllana, le coordinateur du projet. Admire (basede donnes), @Neurist (dtection d'anvrismes), la plupart de nos projets de recherche concernentsoit directement les sciences informatiques, soit la sant . En effet, d'autres traitent du cancers oude la faim dans le monde. Mais leur point commun a tous est qu'il est impossible de prsager dursultat des modlisations, tant le nombre de paramtres peut-tre dcisif.

    Pourtant, dans le cadre du Septime programme-cadre pour la recherche et le dveloppementtechnologique (FP7), l'Union veut investir 9,11 milliards d'euros sur 2007 - 2013 dans la recherchesur les TIC (sur plus de 53 milliards au total). En 2009, elle aura dpense 2,4 milliards sur ce

    secteur, tous programmes confondus. En comparaison, on dpense un milliard par jour pourl'agriculture , prcise Manfred Halver de l'Agence autrichienne de promotion de la recherche(FFG).

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    Les chercheurs sont donc invits cultiver le jardin numrique de l'Europe. Une question decomptitivit...

    Et c'est la que le bas blesse. Car la coopration s'impose dans ces programmes. Quelles applicationspour quels rsultats? Quel partenariat Public/Priv? A Vienne, l'un des sponsors du projet Admire

    dveloppe des logiciels d'entreprise pour la gestion des ressources, (financires et humaines). Cetype d'applications permet, entre autres, de mieux connatre les consommateurs et leurs besoins.D'autres parts, Google pas plus que Facebook ou les jeux vido en ligne, ne fonctionnerait sans les fermes de serveurs .

    Reste que ces ordinateurs sont en fait capables du pire comme du meilleur, car comme l'expliqueDorian Karatzas, responsable thique et Recherche la commission europenne : tout dpend del'utilisation que l'on en fait . La multiplication des donnes, qu'elles soit personnelles ou non, estindniable. Reste que leur administration est encore difficile, et leur protection toujours un

    problme (Ipv6) (3).

    Index :1.http://www.informationweek.com/news/internet/search/showArticle.jhtml?articleID=1978008802.70.000 tudiants, cre au XIVe sicle3.Prochaine gnration d'adresse Internet (IP), trs controverse, et qui identifiera les produitsde consommation.

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    The people behind @neurIST: Geeky nurses? Unlikely.

    Andrei Dulvac

    Andrei, this is Celline, said prof. Siegfried Benkner, head of the Computer Science department at

    the University of Vienna. She may seem small, but she is a powerful thing. Celline is the mainpiece of machinery used in @neurIST, an EU funded research project which aims to help clinicalpatients with aneurysm. Prof. Benkner is the coordinator of the project and he agreed to give medetails and show me around.

    We were in one of the servers room at the university. It was cold, dry and noisy and I startedthinking that Celline liked different things than me. The airflow and temperature are beingmonitored periodically because the machines need this kind of environment in order to work

    properly, said the man louder this time, as we got closer to the computers and the noise built up.The goal of this project is to develop and integrate the IT infrastructure in order to improve thediagnostics and treatment of this disease by merging different kind of data, from literature, research

    clinical data and this new method, computer simulations. This way, we make it much easier fordoctors to diagnose and treat aneurysm, he explained. The project wasnt very clear to me so Ioversimplified things in my mind and thought of the people working with @neurIST as geekynurses with a laptop. This image was soon to be changed completely in my mind.

    Aneurysm is a complicated disease, usually linked with faulty genes, that has to do with a lot offactors and patient background. Diagnostic and treatment is usually done by looking at similar casesof aneurysm. But having access to such cases is a hard thing, even between local hospitals, let alonehospitals in different countries. The @neurIST project aims to make this an easy process. Simply

    put, it gathers, groups and analyses medical data from patients with aneurysm. This might not seemthat hard to accomplish, but it actually is. @neurIST took 4 years (2006-2010), 17.5 million Euros,28 research partners and 20 hospitals to get to this stage, and its still far from being a very mature

    project. The amount of work needed was so large that the project had to be split into 6 modules: 2which deal mainly with the infrastructure (@neuCompute ad @neuInfo), and 4 that deal more withthe clinical practice (@neuLink, @newFuse, @neuRisk and @neuEndo).

    @neuLink deals with finding links between the disease and genetics. With the help of highperformance computers (HPC), information can be found on how and what genes influence theoccurrence and the development of aneurysm.

    @neuFuse tries to define how patient data should be gathered from different sources and how it

    should be stored. This part is extremely important and hard to deal with. Why is it so important?Lets take traditional diagnosis. You have an atypical case of aneurysm. You go to a doctor and hesends you to another one and so on. You end up having 20 doctors. Doctors need to knoweverything about your lab results and your medical history. So your charts have to go from onedoctor to another and this takes time and a lot of administrative effort. Besides that, they cant fullyrely on lab results given by other hospitals so they take some of the lab tests again. And you have togive your history to all of your doctors. This is called data fragmentation and data redundancy.@neuFuse aims to overcome these problems, which always rise when dealing with a lot of datafrom different sources.

    @neuRisk is the project module that provides personalized risk assessment and treatment

    guidelines. Your medical information gets in the system and the system presents this information ina visual, easily interpretable manner. You can see the shape of your blood vessels, you get

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    information about pressure and other things and you also get a risk factor and different treatmentoptions, based on other similar cases that have been processed by @neurIST.

    @neuEndo deals with optimizing and developing medical equipment used in treating aneurysm. Itprovides a very useful tool for simulating the mechanics of such devices, as well as the outcome of

    a medical intervention with the devices that are designed.I left the servers room cold and with a dry mouth. Prof. Benkner felt my surprise with howuncomfortable it could get in there and he explained that people dont get in that often and thateverything is controlled remotely. He offered to show me one of the labs where they develop andtest parts of the project. I said yes.

    The room was bigger than I expected a computer lab to be. There were two people working, each attheir own desk. One of them was looking at a 3D model of a brain, testing the interface. Prof.Benkner explained that some medical information is gathered in real time from hospitals, from real

    patients, but in order to keep the patients privacy, the system hides their real names. Legal andethical issues are a major concern in this project because we are dealing with patient specific data

    and the privacy of this data is a major challenge, from the technical point of view, also. And, ofcourse, the system we are developing has to obey the European law. And its worse than that

    because each European country has its own specific law that we have to take into consideration.This is why we also have legal and ethical experts working close with everyone else in this project.

    I realized then how complex and how hard it is to develop such a system and what I had from thenon was just respect for the people behind @neurIST. I couldnt look at them as nurses, anymore,helping doctors, the real benefactors. And the need for such a system became clear to me. Whenwill we see @neurIST in hospitals everywhere, as we now see the trivial MRI machine?

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    Computer che curano, le tecnologie IT al servizio della medicina nella cura dellaneurisma

    celebrale.

    Priscilla Manzotti

    Laneurisma consiste in una sorta di estroflessione, rigonfiamento di unarteria, che pu avveniresia per cause congenite, che acquisite nellarco della propria vita che possono dar luogo adaneurismi di diverse dimensioni. Lincidenza annuale di emorragie risultanti dalla rottura dianeurismi intracranici stata stimata essere 9 per 100000, una grande porzione di persone chehanno queste emorragie morir o rimarr invalida e quindi dipendente dalle cure di altre persone.Ai medici spetta la scelta della cura, la valutazione di tutti i fattori per decidere se intervenire omeno chirurgicamente.Quale sar la cura migliore? Questa sar la domanda rivolta al programma sviluppato dal progetto@neurIST che vede coinvolto il dipartimento di Scientific Computing delluniversit di Vienna.Il progetto @neurIST (Integrated Biomedical Informatics for the Management of CerebralAneurysms) stato finanziato con un budget di 17 miloni di euro dal settimo programma quadro

    della comunit europea, ha una durata di quattro anni, partito a gennaio 2006, ed unisce istituzionipubbliche e private di 12 nazioni europee.Il progetto si propone di aiutare i medici a prendere decisioni e selezionare il trattamento piappropriato per ogni caso in esame, migliorando la cura dei pazienti, con lobiettivo finale diridurre il numero di trattamenti non necessari del 50%.@neuriIST punta ad un miglioramento della diagnostica, della prevenzione e del trattamentodellaneurisma; permette ad esempio di calcolare il rischio di rottura dellaneurisma nei pazienti eottimizzare il loro trattamento.@neuriIST permetter inoltre di migliorare le conoscenze dellaneurisma (la formazione, la crescitae la rottura ), e trovare le relazioni tra fattori genetici, stili di vita e la malattia.Tutto questo sar reso possibile da uninfrastruttura IT che sar sviluppata per la gestione elelaborazione della vasta quantit di dati eterogenei acquisiti durante le diagnosi.Queste grandi quantit di dati riguardano informazioni distribuite su diversi livelli: dal livellomolecolare (gene e proteine) a quello della persona.@neurIST permetter laccesso a queste informazioni e ne garantir la conservazione, si potrquindi selezionare quando richiesto il miglior trattamento per ogni paziente ad esempio cercandoinformazioni relative a pazienti con simili aneurismi per volume, forma, superficie, stile di vita del

    paziente e base genetica.Il progetto @neuriIST riunisce persone con esperienze e conoscenze diverse, dai medici airicercatori informatici, che lavorano insieme, creando una collaborazione che potr costituire unvalido aiuto nella cura dellaneurisma.

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    I can see, whats in your head

    Triin Tammert

    Scientific computing is today widely used in many fields. Medicine is one of them and it is a huge

    benefit doctors can model and watch items inside peoples heads without the need to first openthem.

    There is an everlasting question: should I rent a house or should I buy one? If I will rent it, I pay forwhat I use and when I need a bigger and better one, I just rent bigger and better house and movethere. On the other hand, if I will buy a house, I will finally own it, but it is not sure, how much it isworth then and can I fit my whole family to this house.Information and communication technologies and scientific computing may seem difficult tounderstand but there are similar dilemmas. Should science lab own a supercomputer or should they

    just rent the access to a virtual supercomputer that scientists can use via Internet? There is achance that they will have so much data, that some day the space in their supercomputer is just

    not enough, so maybe still renting? But there can also be problems are the connections fastenough, etc...

    The terms in scientific computing infrastructures:Parallel systems, supercomputers, that are coupling many processors in a single system;Distributed systems, grids, clouds, that are coupling many computers across Internet (virtualsupercomputer).

    Scientific computing has become third pillar of scientific discovery, complementing theory andexperiment. Computers are used in many fields: weather prediction, financial optimization, materialsciences, transport logistics, molecular modeling, medicine, etc.@aneurIST, an EU-funded medicine project, that connects scientists and doctors from manyEuropean countries. It is a good example of interdisciplinary project that uses the possibilities thatcloud computing offers. You can call it Google model it means having many programs you canuse just by logging in, without installing them to your personal machine (like Google Maps,Blogger, etc).

    @neurIST is focused on cerebral aneurysms and intends to provide an integrated decision supportsystem to assess the risk of aneurysm rupture in patients and to optimize their treatments. Thecurrent process of cerebral aneurysm diagnosis, treatment planning and treatment development is

    highly compromised by the fragmentation of relevant data. @neurIST presents a new paradigm tounderstand and manage cerebral aneurysms. A complete IT infrastructure is developed for themanagement and processing of the vast amount of heterogeneous data acquired during diagnosis.@neurIST benefits patients with better diagnostics, prevention and treatment because it combinesefforts of clinicians and industry. Through research clinicians gain a greater insight in aneurysmunderstanding, while industry will be dragged by these achievements to develop more suitablemedical devices to treat the disease.

    @neurIST provides IT infrastructure that shares biomedical knowledge providing access to a set ofsoftware tools and platforms such as @neuLink, @neuFuse, @neuRisk, @neuEndo, @neuComputeand @neuInfo.

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    One of the reasons, why @neurIST project was born, is that personalised risk assessment couldreduce unnecessary treatment of aneurysms by 50%, with concomitant savings estimated in theorder of several million euros per year.

    This project includes in addition to computer science and medicine also many ethical and legal

    questions, since there are involved patients from many countries, and delicate information aboutpatients (genetical, medical, etc).

    How it really works? Patient accepts (by signing a paper) using his/her data and it is addedanonymusly to the database in the hospital (for example in Barcelona). The software created forthe @neurIST project has access to the database and creates an illusion, that there is one bigdatabase (although actually there are parts of database in different locations and there parts areconnected via Internet). So if now a doctor in the United Kingdom has a patient who has ananeurysm and the doctor wants to compare it with some similar cases, he or she just has to log in tothe database and has the access to all the information.

    Chance to share and compare data helps finding links between genomics and cerebral aneurysmsand helps doctors to take decisions and select more appropriate treatments. @neurIST improvesalso patient care by identifying patients with high risk of rupture by assessing a personal risk factor,thereby reducing the patient's operation risks and anxiety.

    "@neurIST: Integrated Biomedical Informatics for the Management of Cerebral Aneurysms" is aEuropean initiative within the Sixth Framework Programme Priority 2 of the Information SocietyTechnologies IST. This 4-year project started in January 1st 2006 with a 17 million budget,gathering 28 public and private institutions of 12 European countries. Several organizations fromthe U.S.A., New Zealand and Japan participate as external collaborators. @neurIST partners includeindustrial, medical and academic institutions.

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    E-ethicscience

    Enrico Minora

    The common framework in EU means and implies a new method of evolution for cultural

    development and sharing frameworks for scientific added values in international environments.

    The most direct way to ensure a regulation in international matter and contexts is to create softwaresolutions for a cooperation standard and common frameworks of analysis for so called nextgeneration networks. This implies that taking into consideration science rules and laws to support amore modern and integrated method of devolution for ensuring stronger ideas and concepts in anopen knowledge society is the best practice way to strengthen a path in EU systems to enlarge amost advanced society. The importance to define a common E-Science based on cultural datainclusion of common people about information spread and original new rules on technologicalinstruments for cooperation is the only way to settle down a new social frameworks in internationalenvironments. And so the origin of species depends on a generally talking overview about human

    and life sciences integrated on common science standards for a most important and deep technologyusages to enrich people in semantic ways also on ontology ways such as, for example, widespreadhealth new methods to apply E-care and relative methods of analysis to compute necessaryinformation for a best practice regulation over cultural items. Science consists in a more and moreimportant trace given by species evolution itself frame-worked under cultural diffusion aboutscientific data management. Improving new matters and also discovery fields for discussion aboutE-items means also strengthening common ways and leaving more modern traces to ensure aregular and progress in science definition. In these fields of regulation about inter-cultural progressEuropean projects for international integration and inclusion means, on one hand more discussiontopics for common people studying in multi-cultural project such as, for example, MY SCIENCEPROGRAM implemented by European Commission in General Direction for Research andDevelopment, and on the other hand research over a sharing base in ruling most importantdefinitions about common topics of discussion and scientific use of modern tools for largerimplementations in progressive generations and young scientific journalism as source to ensure theEuropean scientific culture diffusion.As a result of this increasingly integration process to affirm new ways to define cultural patterns inthe best way there is also social inclusion for E-countries, such as all European nations generallytalking but also Eastern ones in a specific way to get a propulsive translations of their languages andscientific expressions in the Euro-area framework. Moreover the only approach for a good qualityoutput on this area is reaching a general overview about definitively useful new generationalstandards and expression in the way of a more -la-page common and generally valid rule for

    international cooperation and progress both in science and society. In conclusion ethics in science isthe best way to strengthen a progressive parameter over both general and specifically technicalapproaches in all cultural fields.

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    Internet Computation Technology:

    Web 3.0 path through computing science upgrade

    Enrico Minora

    After more than ten years history of Web 2.0, it is necessary to implement a new system of toolsintegrated in a more modern operative platform as for ICT new semantic definition approach andbest performance evolution of most common adaptive instruments for users' labor and technicalmethods of new software and hardware combinatorial solutions

    Internet evolution steps from a social networking level of exploitation to more complex andsophisticated in integration interoperability outputs in defining a usable technique of development

    both for simpler and more advanced characteristics of analysis. Cooperative networks give origin tomany new possible interpretation and functional adaptations to the historical upgrade of society andeconomic modern systems by taking inspiration from a new ruling role of World Wide Webinstruments scientific-based.

    The best standard to accept a re-definition of Internet is the same acronym WWW, that means a 3Wor, anyway, Web 3 application of knowledge information systems integrated in new kinds and waysto combine data processing and computational technology. This means that, according to thehistorical value given to computerization and present world applicable scientific studies andelaborations about data mining inside of economical and social evolution enlargement processes fordeveloping a deeper inside technology method for analysis, IBM sector estimation - that meansInternational Business Machines even interpretable as a convert towards an Internet Best Modelsolution - over health-care 5,4% costs cut by new electronic systems applications (E-Health,European Health or Electronic Health) is also extensible to the environmental field by USobservatories over renewable energy studies already studied at Stanford University under thesupervision of Web marketing expert Ward Hanson. This combinatorial model takes inspirationfrom HWS definition as up-grade Health Web System gaining sunk costs reduction by servicevirtual care methods based on ICT compliance, attitude and technological automatic calculation oftherapy.As for environmental framework of study, in the European Union so called 20-20-20 targetimplementable as a 20% CO2 emissions reduction by renewable energy solutions can be combinedwith US 2030 objective to define as a WWS (Water, Wind, Sun) model meaning hydroelectric,Aeolian and solar resources path. All of these kinds of clean solutions can be implemented by greenIT implementation as for the equalization between WWS and WWW with Sun element as Web partfor new policy developments.According to UStanford elaboration described by December 2009 number of Scientific American,

    renewable energy world consumption will consist in 11,5 Terawatt (TW) that means: 11,5 TW =WWS => 11,5 T = WS. 11,5 T coefficient unit implies a 5,4 T energy net cost reduction by newICT models up to a global 16,9 Terawatt employ. So 5,4 element is to be considered a datacomputational base to analyze and apply useful criteria for both policies and create a convergence

    between 2020 path and 2030 trend. T can be considered the Technology constant and also Trend,calculation basis and unit for determination of the benefit of correlated interventions over bothhealth and energy matters. And in the model we can infer also a translation from '20 to '30 horizonsof common intervention recalling transition from a number 2.0 Internet environment to best 3.0applications.

    (Data processing elaboration has been made at University of Vienna laboratories during MY

    SCIENCE PROGRAM - Research and Development Direction of European Commission - onDecember 2010)

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    Bio-medicine and relative E-care computer-based therapies

    Enrico Minora

    Taking care of many kinds of diseases consists in a great variety of interventions based on smart

    grids and advanced operations based essentially on multi-core applications and even preventiongiven up by bio-pharmaceutics and information technology applied to genomics and cellcalculations

    The main purpose of most advanced medical E-care activity and therapies is to settle down a usefulquantity of health operations based on computer science methods of intervention. As a matter offact, the origin of greater part of diseases is given up by a scarcely deep knowledge of healthtroubles conditions such as, for example, a low level of information about the treatment or also agap in mind data processing due to a problem source gap. So the best way to practice goodmedicine depends essentially on both good and rational kind of action over disease generated by acomputer data elaboration of the way to get a sufficient impact over the gap to be filled.

    As a consequence of this intelligent modern E-care intervention method, one possible instrument tobe applied consists in a precise strategy for a competent therapy application on the patient. Firstlythis modus operandi can comprise a virtual simulation of health operation in due diligence with data

    privacy respect and context conditions for a good information interoperability between the doctor(agent) and the patient. This last stakeholder is basically influenced by the environment of therapyapplication also taking into consideration that same intervention needs to be applied in proactivecontext conditions. The direct effect of a good framework situation in developing attitudes to getsuccess in the operation is an important part given by an advanced way for disease impact reductionand technical evaluation of health mission critical information contained in the therapy.A basically important influence over patient ability to leave her/his health diseases in a successfulway is the h-data processing impact of E-care systems integrated by modern instruments such as,for example, smart grids and bio-molecular treatments consisting in computer cell-based relativeelaborations. All of this variety of care styles is originated by a key-solution to be spread in terms of

    practical impact and psychological centrality of prevention. This last main operational approachcomprehends just health information processing in its so many relevant fields of applications givingorigin to a variety of action methods. In concrete terms, University of Vienna Computing ScienceDepartment supercomputer is able to manage a great quantity of data by mainframe calculation

    power based also on an open source E-health platform widespread as policy impact all over Europeby neurIST applied research E-project. Both data system integration and therapy solutions arelogistically linked by interoperability information treatment and just-in-time interventions in deepknowledge of most modern health therapy criteria and strategies.

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    Movie of Kristina Medic about @neurIST can be found on:http://www.eurac.edu/it/newsevents/webtv/pages/default.aspx?mediaid=44981&page=1

    http://www.eurac.edu/it/newsevents/webtv/pages/default.aspx?mediaid=44981&page=1http://www.eurac.edu/it/newsevents/webtv/pages/default.aspx?mediaid=44981&page=1