This week I will be updating this post because I am reading a lot of papers and I need a way to track them. Following the same structure of last weeks I leave some links to the activities I am carrying out:
I have focused on some interesting subjects Statistics (Bayesian networks), Data Streams, Feedback Control Loops, Autonomous Computing and e-Learning systems (this is just for personal interest). I have started, and finished, the next list of papers and books:
Writing and reviewing
I would like to leave the link to an article about “How to review a paper
“, an excellent guide to evaluate your reviews and take into account your responsibilities as reviewer.
Coding and Tools
I have not made any relevant progress in developing tasks but I have being refreshing my know-how on R.
I have finished the evaluation of alumni in Health Information Systems and I am very proud of the marks and the work carried out by student during the last months. I have some links of their works building mashups but I prefer do not leave here the links due to privacy issues.
This week has elapsed very fast and I have made a lot of things that I leave bellow:
My main concern in the research is how can I address the automatic computation of a lot of sensors (applications, cloud management platforms, etc.), i.e. how can I monitorize resources? and which the variables to be taken into account are. In this sense I have read some papers from my colleagues at SEERC and other authors:
The main outcome of this work has been an small presentation about how to process Big Data applying the Lambda architecture
, more specifically adding semantic to this process. It is a just a proposal and first thinkings but I will do my best to debug and design the whole process.
I have made some progresses in the article about the experience publishing the “Webindex” as Linked Data and I have also planned the potential articles for this year and their contents.
Sometimes you feel very motivated to test new tools and frameworks and I am now in this phase:
I have finished the evaluation of Health Information Systems in Nursing and Physiotherapy course at the University of Oviedo. They have developed very good works applying Web 2.0 concepts for building mashups in the Health sector, I am very proud of all students.
Here it is where I spent most of the time (and thanks to my colleague Fotis) but I finally got (almost) all the required documentation:
I believe something is missing but, anyway, it is just a summary…
As you may know I am starting a new stage in a new country and institution. Now I am a Marie Curie Experienced Researcher (Postdoc) working at SEERC in Thessaloniki, more specifically in the RELATE-ITN FP7 project. My research will be address some topics such as stream reasoning, cloud computing, big data, etc. to create a system for monitoring QoS in cloud computing environments and service oriented architectures. As far as I know the objective is to get information about applications on the cloud and verify that the current status of different variables are aligned to SLAs so it is necessary to continuosly gather data from applications, promote to an existing knowledge-base and check restrictions through reasoning processes for finally making decisions such as new provisioning, etc.
This first week I was adapting to my new office and I would like to thank you to all administrative staff and colleagues from SEERC for their warm welcome! I am very motivated. My work during this first week was focused on reading papers, testing tools and coding some prototypes. Following I am going to leave a summary of my activities:
Reading (specs, research papers and books)
- I am finishing a technical report abou our work in the Webindex project
- I am starting to write some papers in different topics that I will announce as soon as they are finished
Development and testing
- I have made a simple Python prototype to partially transform the Webindex in DSPL. The result can be found here. It just is an small example of consuming Linked Data.
- I have integrated Git, Heroku and Travis for creating a quality development environment as Labra suggested and I have to say it really works fine!
- I have made my first prototype with Drools Fusion processing events
- I have made some tests with C-SPARQL
- I have made my first prototype with Grails
- I have downloaded, compiled and deployed the current version of Apache Stanbol.
- I have started to use Cosm (an IoT platform)
- I have deployed the CommonCrawl prototype in Amazon EC2 Elastic Map/Reduce
- Some interesting presentations at
- I have created accounts to monitorize cloud computing applications in the next platforms (of course you need, in most of cases, an Amazon EC2 account):
- I have also created my profile at W3C Community and joined the next groups
- Cloud Computing Community Group (homepage)
- Data Driven Standards Community Group (homepage)
- Decisions and Decision-Making Community Group (homepage)
- Development Linked Data Community Group (homepage)
- Semantic Open Data Community Group (homepage)
- Semantic Sensor Networks Community Group (homepage)
This is more or less what I have been doing this first week, I think I have improved and refreshed part of my know-how and I have also designed a first version of “A semantic-based lambda architecture for QoS Management in Cloud Computing and Service Oriented Architectures” that I will present on Tuesday.
Let’s rock it!
A tweet post…
I was creating my profile at Google Scholar and I could add some of my publications (it is not yet the complete list but most of them are now available).
Another tweet post…
I have also created a dashboard in Scoop.it to track and curate contents about some of my research interests such as cloud computing, stream reasoning, computational social choice theory, opinion mining or sentimental analysis.
Last weeks I have reviewed some of the existing works trying to mix semantics and cloud computing to improve some of the key-processes in a cloud environment. QoS and resource provisioning are two of the main processes that are supposed to take advantage of an intelligent decision support systems to dynamically adapt client requirements to cloud resources. According to the different types of cloud (SaaS, PaaS and IaaS) the use of formal models and knowledge bases can help to take decisions in different ways: prediction of resources, adjustment of “pay-as-go”, etc. Among other works I would like to leave here a list of relevant papers, etc. that I consider essential to understand the underlying problems, technology, current efforts and approaches to tackle them.
I will continue updating this post and the references but I think it is a good starting point to check all related works in this area. Moreover I had collected some papers related to Map/Reduce, SPARQL and more in the ROCAS project wiki.