What contribution can automated reasoning make to e-Science? Marta Kwiatkowska School of Computer Science www.cs.bham.ac.uk/~mzk ARW’05 panel

Let’s begin with definitions Science: a method of learning about the physical universe by applying the principles of the scientific method, which includes making empirical observations, proposing hypotheses to explain those observations, and testing those hypotheses in valid and reliable ways; also refers to the organized body of knowledge that results from scientific study e-Science computationally intensive science. It is also the type of science that is carried out in highly distributed network environments, or science that uses immense data sets that require grid computing. Examples of this include social simulations, particle physics, earth sciences and bio-informatics.

So it is about a transition from…

To this…

What enables e-Science? Data sharing: distribution, query searches, curation Distributed databases Web-services Ontologies Collaboration: coordination, concurrency control Collaborative protocols Workflow Web-service orchestration Compute power: scheduling, , load-balancing, performance Computer clusters Campus Grids Large-scale grids

The e-Scientist of the future Will this work? The Internet Remote access to high-performance computers, via Internet Remote access to visualisation facilities, via Internet Computational steering from anywhere, via PDA Visualisation, on your laptop Fast, online, accurate, … WiFi sales grow exponentially Bluetooth new technology Intereference claimed in http://glennf.weblogs.com/discuss/msgReader$11,http://www.extremetech.com/article2/0,3973,66509,00.asp But not in http://www.thinkmobile.com/News/00/45/56/ Use the same frequency range, but 802.11b uses channelisation of range (sends large data packets) BlueTooth sends small packets and uses frequency hopping (more frequent than WiFi), hence BlueTooth can react and bring WiFi down 2.4Gz range used is unregulated, microwaves can emit noise in that frequency

The pi-calculus example Biztalk Based on pi-calculus Verification of security policies Use ProVerif, pi-calculus tool Biological processes Stochastic pi-calulcus What is special about pi-calculus? About processes and dynamics Formal semantics, rigour Matches the software/systems trends: dynamic, mobile, interacting, reconfigurable Automated tools!

Contribution from automated reasoning Computer systems-related More of what is already being done – databases, distributed systems, collaborative environments – but larger scale! Distributed coordination, concurrency control, databases, performance, etc New challenges Science-related Rigorous computational foundation for modelling process dynamics, e.g. biological systems Study of fundamental principles Modelling – process calculi, automata, logics Analysis, simulation, model checking, Theory and tools

Modelling and Analysis Iterative cycle of Hypothesis forming, modelling, analysis Experimental validation, feedback Methods of analysis Simulation Automated verification, e.g. model checking Probabilistic verification Formal reasoning Key goals Realisation, when model consistently produces outputs that cannot be falsified by biological experiment In-silico prediction of organism’s response Automation of the analysis process

What is computer science? The systematic study of computing systems and computation. The body of knowledge resulting from this discipline contains theories for understanding computing systems and methods; design methodology, algorithms, and tools; methods for the testing of concepts; methods of analysis and verification; and knowledge representation and implementation.

Computer Science contribution Formal languages and models Principles and interaction primitives specific for biological processes Hybrid models for continuous and discrete dynamics Reasoning frameworks to establish important properties Control-theoretic techniques for robustness Automation of analysis: research leading to the tools Efficient algorithms, for bioinformatics, analysis Quantitative and qualitative model checking Grid computing, e-Science Scalability Model reductions, abstraction Hierachical decomposition Compositionality