Yesterday I attended a “Music Information Retrieval from a Multicultural Perspective” meetup in SoundCloud offices. It was one of the most thought provoking meetups I have attended in a long time. Prof Xavier Serra, who gave the talk has a lot of experience with Music Information Retrieval and with community projects along with industrial projects – dunya, acousticbrainz, compmusic and more.
I have just read “Data Driven – creating a data culture” by Hilary Mason and DJ Patil.
While computer science is considered a new science or a new discipline data science is even a newer one. Well is it? Is it a discipline? What is the goals of data scientist and data science team within different organizations? Where should they place? What are their responsibilities and how is success measured?
For me it seems that data science is in the phase of Kuhn’s pre-paradigm and Mason and Patil tries to move it in to the phase of normal science. They argue about the place and limitation of data science, what are the characteristics of data scientists. Maybe most importantly they talk about how to measure success and how to set goals to data science process.
So what about Weber?
In this lecture, Weber talks about the advantages of choosing an academic career versus an industry career. He also compare between the university systems in Europe and in the US. Almost 100 years has passed since then and the world slightly changed, including the role of work in our life. I think that for many people working in the industry as data scientist has both the advantages of being a scientist (doing some research) and working in the industry (salary, technology)… But I’m not sure if it is a really a “science”. For me personally this title or definition is not important – I love what I do and it creates a measurable value to the organizations I work for.
I see many of the processes suggested in this book as trying to bridge between and academic life and the industry life.
Over all, this hand book was ok, but I expected a bit more.