In 2014, infrastructure components such as Hadoop, Berkeley Data Stack and other commercial tools have stabilized and are thriving. The challenges have moved higher up the stack from data collection and storage to data analysis and its presentation to users. The focus for this year’s conference on analytics – the infrastructure that powers analytics and how analytics is done.
Talks will cover various forms of analytics including real-time and opportunity analytics, and technologies and models used for analyzing data.
Proposals will be reviewed using 5 criteria:
Domain diversity – proposals will be selected from different domains – medical, insurance, banking, online transactions, retail. If there is more than one proposal from a domain, the one which meets the editorial criteria will be chosen.
Novelty – what has been done beyond the obvious. Insights – what insights does the proposal share with the audience that they did not know earlier. Practical versus theoretical – we are looking for applied knowledge. If the proposal covers material that can be looked up online, it will not be considered.
Conceptual versus tools-centric – tell us why, not how. Tell the audience what was the philosophy underlying your use of an application, not how an application was used. Presentation skills – proposer’s presentation skills will be reviewed carefully and assistance provided to ensure that the material is communicated in the most precise and effective manner to the audience.
For queries about proposals / submissions, write to email@example.com
Data Collection and Transport – for e.g, Opendatatoolkit, Scribe, Kafka, RabbitMQ, etc.
Data Storage, Caching and Management – Distributed storage (such as Gluster, HDFS) or hardware-specific (such as SSD or memory) or databases (Postgresql, MySQL, Infobright) or caching/storage (Memcache, Cassandra, Redis, etc).
Data Processing, Querying and Analysis – Oozie, Azkaban, scikit-learn, Mahout, Impala, Hive, Tez, etc.
Big data and security
Big data and internet of things
Data Usage and BI (Business Intelligence) in different sectors.
Please note: the technology stacks mentioned above indicate latest technologies that will be of interest to the community. Talks should not be on the technologies per se, but how these have been used and implemented in various sectors, enterprises and contexts.
Scaling Spatial Data - OpenStreetMap as Infrastructure.
For the success of any location service, the length and breadth of geographic relationships have to be recorded with enough room for frequent verification and classification. This talk will introduce the infrastructure behind the largest open geographic data repository - OpenStreetMap - and how you can leverage the complete geospatial stack for independent data collection, verification, and building services. We will understand and discuss the unique data model, its performance, scalability, data editing and verification methods, and extensible data service built on top of it. Besides, we will learn what it means for serving beautiful maps from this unmatched dataset and end with my experiences on a recent project that I worked on which uses OpenStreetMap from ground up to monitor natural resources extraction in the Democratic Republic of Congo.
OpenStreetMap has over 9 years of lessons in managing large scale crowdsourced spatial data with open source infrastructure. The project now has over 1,600,000 contributors out which about 3000 users map every day. They create over 16,35,608 nodes. The changes are replicated across several official and unoffical instances and all the maps rendered with OpenStreetMap data are updated in under a minute on the Internet.
With PostgreSQL and PostGIS as the backbone of data storage, OpenStreetMap has created an ecosystem of tools that is now available for anyone to use for different kinds of spatial data. The data can be processed, queried and styled in several ways. We will discuss setting up the OpenStreetMap infrastructure for custom data models and explore the edit-style-render toolchain. There is a rich API and database dump/restore mechanisms that is built into the infrastructure. OpenStreetMap also takes quality assurance seriously that there is a process in place for identifying and rectifying vandalism or errors.
Fair understanding of Unix, Databases, and Networks.
Sajjad Anwar is a hacktivist and programmer based in Bangalore. He works in the research and design of data infrastructure, analytics and infographics. Being involved with OpenStreetMap for over 5 years, he has extensive experience working with spatial data and advocates open geographic data. He helps organisations to build and maintain their data infrastructure. He is found working with other technologists, social activists and researchers in education, human rights and policy making. Along with two others, he runs the geohackers.in collective.