“It’s more fun to blame things than to fix them” said Dr P.G Bhat, a retired naval officer and a software professional, and now an educationist and a social worker.
This week, students of IID, swam deep into the questions upon the functionality and the working of the Election Commission of India. Simple data sets could stir the national system and in the end all were stirred up with energy and left bowled over with his enthusiasm and passion to tick out little errors with his witty numbers. He sees the world around him as a big code with some simple bugs.
We live in a world where our identity is enveloped in an 8.6 cm X 5.4 cm PVC laminated sheet of paper, i.e., the voter ID card. So any discrepancy there, resonates exponentially on the Indian picture.
He talked about the importance of standardization and simplification electoral data set In India.
India, a country of 1.2 billion people, where identities are quantified. We might live by our names (conventionally) followed by our surname but our country identifies us by our EPIC number i.e. Elector’s Photo Identity Card number. This data before being carved out into a form has to be extracted, transformed and then finally, loaded in order to be processed, which might be erroneous at times.
According to him, miscellaneous errors in technical tools to extract them, errors in reading various Indic texts, variations in the file format/names, etc. keeps us away from harnessing this data perfectly. On that note he also quotes,
“In India, The data set is digitally born but physically used in electoral purposes”
While analyzing data, metadata should be honored and represented properly, according to the conventions and standards. It should be indexed and easily accessible. (For example, only KA should be used for Karnataka but not KN)
“Simplification is another area where we, as data analysts/visualizers, should concentrate on the normal users. Transliteration is another important factor. High level of quality analysis should also be considered while data mining and data modelling.”
“It’s in the smell” he said, while putting the lecture to an end. When you seek a data set, when you listen to an inference, when you stumble upon something fishy, you smell the ingredients and analyze its quality with precise quantity and then serve your hungry mind.
“Get your facts first. You can distort them later.” – Mark Twain