Aug 13 2013

Three research questions for big and open data

CarlaBoninaOn the 1st and 2nd of July 2013, the LSE hosted the second New Economic Models in the Digital Economy (NEMODE) Community Meeting. In this post, LSE Tech fellow Carla Bonina shares the three research questions that emerged as part of the big and open data group: the value of open data, the labour market needs for profiting for big data and the ethical implications from experiments using big data.

During the first days of July, we welcomed the second NEMODE+ community meeting at the LSE. NEMODE+ is a network initiative funded under the Research Councils UK Digital Economy research programme that brings together academics and practitioners to explore new economic models in the digital economy. During the first day, we heard insightful updates on projects that have already been funded by the NEMODE+ network. Day one also covered the overview of eight new projects that have been funded as part of NeMinDE, a sister initiative under the RCUK Digital Economy programme.

Day two was a hands-on project. One of the objectives of NEMODE+ is to stimunemodemeeting_bigdatagrouplate new ideas, propose areas of research and policy engagement around the opportunities and challenges that digital technologies bring to the UK economy and society. Therefore, part of the activities of day two included working in groups around six areas of interest proposed by the delegates in advanced. I took part in the sub-group clustered around big and open data, along with four colleagues from other institutions. As a result of the brainstorming exercise, we arrived at three main research questions that were later presented to the whole community. I share these as follows with a brief explanation of the sub-set of questions or issues to address.

  • Research Question #1: What is the value to the UK of open data?

Under this question, we agreed that at least two themes need further research development: one is the need to broaden our vision on value constellations and social benefits. In other words, we need to look at the economic, social, political and environmental dimensions of value creation from the use of open data. The other theme that needs investigation is the critical aspects of open data: understanding the tensions, issues and challenges that emerge for the nation, organisations and citizens (i.e. privacy, surveillance, discrimination).

  • Research Question #2: What skills and capabilities do UK organisations need to create value from ‘big data’?

We discussed many topics emerging from big data. Our consensus was that in order to create economic and productivity value for UK firms, a review on the skills, education policies and specific training is needed. New skills include all stages of big data management (i.e. data collection, data analysis, using big data for business operations, using big data in strategic decision-making), and we need a better understanding of what is out there in terms of job qualifications, what is needed and what is missing.

  • Research Question #3: What are the opportunities and ethical challenges for randomised controlled experiments (RCTs) around ‘big data’?

One of the potentials of big (and open) data relies on business intelligence. We suggested that public and private sector organisations will make greater use of big data to run RCTs to test business and public sector offerings. We also agreed that, while these experiments may be a powerful way of getting evidence about what it works, they also raise ethical concerns. We therefore proposed to look more carefully at the design of the RCT itself, and also the implications on how RCT data is used to guide business and policy decisions.

 

Overall, the two day event was insightful and inspiring. You can access the overview of the meeting and the questions of the other groups in the interactive EPSRC website, that is part of the EPSRC Information and Communications Technology project. Also, check the highlights and conversations that we shared on twitter during the two-day event.

Image credits: EPSRC ICT Perspectives Network

This article gives the views of the author, and not the position of the London School of Economics.

We welcome your comments! Please take a look at our comments policy

 _________________________________

About the author

CarlaBoninaCarla BoninaLSE Department of Management
Dr Carla Bonina is a Research Fellow at the LSE Department of Management. Her research interests focus on thinking critically about open data and open government, big data, and value creation and appropriation in the digital economy. She holds a PhD in Management from the LSE. Carla is also the founder and managing editor of the LSE Network Economy Blog.

This entry was posted in big data, business models, Carla Bonina, digital economy, innovation, LSE Tech, Nemode+, open data, Research, social media, Workshop briefing. Bookmark the permalink.

One Response to Three research questions for big and open data

  1. Diego says:

    Fantastic questions. Really eager to see what type of discussion this generates.
    In general terms, the qualitative value of Open Data for Local and Federal Governments has been described as follows:
    – Compliance with Transparency and Accountability mandates. Though this is of value, it is a ´check´ for some governments.
    – Politics. Yes, it is clear that some politicians and political parties benefit of the Open Data momentum. Transparency is always a positive thing to attach to

    Up to now, not much ´real value´ obtained from Open Data. The next points illustrate a bit more the value creation that can happen as Open Data becomes an integral component of how Governments operate:
    - Engagement 3.0. With Open Data new raw data becomes usable engaging private sector and developers. And some of this raw data becomes raw material in citizen friendly apps that engage them in the conversation. Engagement brings collaboration which can be somehow quantified in the equation. And engaging is probably a core tenant of what governments SHOULD do.
    - Innovation. As described in Citizenville (book by Gavin Newsom) Governments have limited resources to do a lot of things. It is not a good idea for Governments to think that they will be able to deliver ALL the innovation that citizens request. By Opening Data Governments can leverage Civic Hackers, their energy and knowledge to then generate valuable apps that Government would have not been able to deliver in time.
    - Efficiencies. FOIA requests have a clear cost that can be reduced via Open Data. Government Communication has a cost that can become more efficient as Open Data becomes part of the communication channel. And lots of apps that can make IT Departments more efficient will surge. Finally, better and easier collaboration between Gov Departments as they can now see the data that other departments have will also be very valuable (and quantifiable).
    - Data that can allow better decision making. Having a lot of Open Data that is well displayed and that can tell stories has the potential of certainly helping in decision making. Governments will benefit from grabbing Open Data and from bringing all their data to help them (in collaboration with citizens) in making decisions.
    - Finally, New companies leveraging on Open Data will contribute via taxes. The GPS and Weather Open Data examples have already been used tons of times. Government Open Data can generate industries with profitable companies that can contribute to the traditional revenues that Governments collect.

    And though this is not for now, there is some potential for governments to generate new revenues purely based on Open Data. This has been seen in other industries. Though raw Government data has to be free for citizens, value added data that has had a process and a packaging before it can be consumed, or data that is consumed with very high frequency via API programs can be monetized.

    More later…

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>