The involvement of women as members of the ICT workforce, as users of ICT products and as designers of ICT developments, have attracted attention of both academia and practice. When the field of information and communication technology (ICT) emerged, many saw it as an area that would especially attract women. Unfortunately, research shows that many countries face under-representation of women in ICT, particularly in decision-making and leadership positions. With the increasing influence and pervasiveness of ICT in modern society, it is especially important to include both men and women perspectives in ICT development. In this regard, one of the main motivations of ICT companies is to boost innovation and creativity through gendered diversity. This makes the problem of women’s understatement of great importance in this field. Here we explore and discuss this problem.
This talk presents the final results of a study among four large ICT organizations in the Netherlands.
Date & Location: Tuesday, 12th February 2014 at 19:00-22:00, IntertainLab at the VU
About PyLadies AMS: PyLadies is an international mentorship group with a focus on helping more women become active participants and leaders in the Python open-source community through education, conferences, events and social gatherings.
Pyladies is organized in 23 local chapters in several cities of the US, Europe, Asia and Africa. The Amsterdam chapter (http://www.meetup.com/PyLadiesAMS/) has been founded in Summer 2013 and it has already organized 4 meetups. Each of these meetups consisted in an evening social event with 3-4 talks on Python programming, tutorials on libraries for particular applications (e.g. data mining) and general best practices in software engineering and attracted around 50 participants.
Sponsors: Thanks to the Computer Science department and the Network Institute (http://www.networkinstitute.org) for sponsoring this event.
For more information: You can post a comment on http://www.meetup.com/PyLadiesAMS/events/156263982 or email: firstname.lastname@example.org
DATE: Mon 24 February 2014
ROOM: Intertain Lab
HOST: Prof. Dr. Patricia Lago
Gathering empirical knowledge is a time consuming and error prone task while the results from empirical studies often are soon outdated by technological solutions. As a result, the impact of empirical results on software engineering practice is often not guaranteed. The empirical community is aware of this problem and during the last years, there has been a lot of discussion on how to improve the impact of empirical results on industrial practices. The discussion often focused on the use of data mining techniques and analysis of software engineering data, and the concept has often been labeled as “Empirical Software Engineering 2.0”.
Starting from the current status the discussion in this specific topic, we propose a way to use massive data analysis as a problem-driven data analysis technique and, more important, as a mean to improve the knowledge sharing process between research and industry. Our assertion is that automatic data mining and analysis, in conjunction to the emerging concepts of lean economy, wisdom of crowds, and open communities, can enable fast feedback cycles between researchers and practitioners (and among researchers as well) and consequently improve the transfer of empirical results into industrial practice.
We identify the key concepts on gathering fast feedback in empirical software engineering by following an experience-based line of reasoning by argument. Based on the identified key concepts, we design and present an approach to fast feedback cycles in empirical software engineering. We identify resulting challenges and infer a research roadmap in the form of a list of open research and engineering challenges.
Our results are not validated yet as they need a broader discussion in the community. To this end, our results serve as a basis to foster the discussion and collaboration within the research community.
Antonio Vetrò is a postdoctoral research fellow at TU München (Germany). He got a Ph.D in Software Engineering at Politecnico di Torino (Italy) in 2013, and has been junior scientist at Fraunhofer Center for Experimental Software Engineering, MD, USA, in 2011. He is specialized on empirical methodologies and analyses of process and product data.
You can find the slides of his talk here.