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DIstributed Computing Environments (DICE) Team
We are a group of computer scientists and IT experts from the Department of Computer Science AGH and ACC Cyfronet AGH. We are a curiosity- and research-driven team, specializing in large-scale distributed computing, HPC, Web and Cloud technologies. We develop new methods, tools and environments and we apply these solutions in e-Science, healthcare and industrial domains.

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Common Information Space (CIS)

Data streams from sensors (e.g. dike sensors, volcano sensors) need to be processed in various ways in order to analyze a current trend, make a prediction, validate a model, or recommend an action. Applications that do this processing, implement sophisticated simulation models and are computationally intensive. Furthermore, in emergency cases the results need to be delivered in real time in which case urgent computations might be triggered automatically and require rapid access to large computing power. In order to satisfy those demands, an infrastructure is needed to manage access to the underlying computing resources, to run high-performance or high-throughput computations which process sensor data streams and to guarantee sufficient computing power for urgent computations. In addition to such an infrastructure, an environment is required to enable end users to define and execute applications, specify sensor streams to be processed, review simulation results and make decisions.

Common Information Space is an infrastructure for high-performance and high-throughput processing of sensor data streams and an environment for end-users to run applications and manage their results. The most important modules of the Common Information Space are: (1) Execution framework, (2) Data and computation access services, (3) Provenance services, (4) Application management environment and (5) Application development environment.


Publications related to CIS

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Common Information Space posters and flyers

cis_poster_2012_sThe Common Information Space: A Framework for Early Warning Systems (2012) (A4, A1), Bartosz Baliś, Tomasz Bartyński, Marian Bubak, Grzegorz Dyk, Tomasz Gubała, Marek Kasztelnik; poster presented during 8th IEEE International Conference of eScience; 8-12 October 2012, Chicago, USA.




cis_poster-cgw11_A4_sCommon Information Space – a Framework for Service-Oriented Scientific Computing (2011) (A4, A0), Bartosz Baliś, Marek Kasztelnik, Marian Bubak, Tomasz Bartyński, Grzegorz Dyk, Tomasz Gubała, and Piotr Nowakowski; poster presented during Cracow Grid Workshop 2011; 7-9 November 2011, Kraków, Poland.




uf-cyf-modelingA4_s.pngMethodology and tool supporting cooperative composition of semantic domain models for experts and developers (2011) (A4, A0), Maciej Rząsa, Tomasz Gubała, Marian Bubak; poster presented during Cracow Grid Workshop 2011; 7-9 November 2011, Kraków, Poland.




cis_general_poster_1_sCommon Information Space (2010), Bartosz Baliś, Tomasz Bartyński, Marian Bubak, Tomasz Gubała, Marek Kasztelnik and Piotr Nowakowski; poster presented during Cracow Grid Workshop 2010; 11-13 October 2010, Kraków, Poland.





Common Information Space deliverables


Common Information Space presentations


Demo movies

Below you will find a list of CIS demos.



  • Common Information Space (CIS) – is a software framework facilitating the creation, deployment and reliable operation of Early Warning Systems. As an example, in a flood early warning system (1) dikes are monitored in real time using wireless sensors, (2) data from the sensors is analyzed in order to detect anomalies or compute dike breach risk, (3) analysis results are assessed to decide whether an emergency situaion has occurred, (4) if assessment indicates an emergency, the system either recommends or automatically takes actions.
  • Early Warning System blueprint – is a template for a specific type of EWS (e.g. for flood monitoring). An EWS blueprint is essentially a set of software artifacts.
  • Early Warning System (EWS) instance – is a specific EWS, configured for and deployed in a specific setting (e.g. for a specific dike managed by a specific organization) and running. An EWS instance is created from an EWS blueprint. There may be multiple instances of the same EWS running in parallel (and perhaps hosted by the same CIS). Those instances may perform the same activities (e.g. dike monitoring) but in different configurations (e.g. different sections of a dike or different dikes).
  • Early Warning System building blocks – the Early Warning System, as a software system, comprises the following components: (1) Appliances, (2) EWS Parts, (3) External components. CIS provides infrastructure services to organize these components into a running system.




      1. Appliance – is any piece of software wrapped into a virtual machine image and exposed as a service which means it can be invoked over the network. Appliances are the most basic building blocks for specific early warning systems. For example, in a flood early warning system appliances wrap legacy scientific applications for (a) analysis of sensor signals using artificial intelligence algorithms, (b) computation of dike stability, (c) computation of water flow through a dike breach, and (d) inundation modeling. The Appliance is a virtual machine image that contains a single program installed on a minimal operating system (i.e. only libraries and services required by the program are installed). Appliances run on physical servers and can be moved across them. Upon startup, the virtual machine is provided with an initial configuration that includes VM-level and program-level data. The former may include, for instance, network configuration data (DNS servers address, gateway etc.), while the latter provides data required by the program to serve a request (for instance: the section of the dike to monitor, how to fetch input data or where to produce results).
      2. Early Warning System Part (EWS Part) – orchestrates data and control flow involving one or more appliances in order to provide a high-level EWS-specific service. The EWS part consumes some input data, invokes appliances and executes a workflow between them. Finally, it is responsible fo publishing its results. For example, in a flood early warning system there is a part which integrates two appliances – computation of water flow through a dike breach and simulation of indundation – in order to provide a high-level service for computing terrain inundation due to dike breach. EWS parts can be created in any supported integration language (e.g. workflow, integration/business rule). Every EWS contains one or more EWS parts which are independent and communicate through the message bus. EWS parts also fulfill other important tasks: data transformations between appliances, asynchronous receipt of messages, computation of alert levels, provenance logging and self-monitoring.
      3. External Component – is a producer or consumer which, while not managed by CIS, exchanges data with the Early Warning System. Examples include sensor data sources, user interfaces, etc.
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