Posts Tagged ‘Cyberinfrastructure’

Geospatial Cyberinfrastructure and User-centric HCI

Friday, March 23rd, 2012

Usability evaluation of GIS is delineated by Haklay et al. in their publication 2010. The connection of human computer interaction (HCI) and public participation geographic information science (PPGIS) is delineated in their paper, but the relationship with geospatial cyberinfrastructure is not explored enough. I think the idea of user-centric design can also be applied in geospatial cyberinfrastructure, which has attracted more research interests.

Geospatial cyberinfrastructure, which provide the functionalities of geospatial data collection, management, analysis and visualization, adopts pure system-centric design in previous studies. Due to the fact that most users of geospatial cyberinfrastructure are research scientists or domain experts, geospatial cyberinfrastructure is criticized for its bad usability. As the development of PPGIS, more users become geospatial data producer in GIS. Since these data are valuable in GIS study, geospatial cyberinfrastructure should be adapted to provide user-centric services.

Here, I name a few challenges for utilizing user-centric design in geospatial cyberinfrastructure, especially when we consider better HCI. Firstly, data search within geospatial cyberinfrastructure should be equipped with fuzzy reasoning functionalities to help non-professional GIS users to fetch the data that they need. Secondly, at the visualization layer, the display should be easy to understand (I think GoogleMap has provided a good example) and manipulate for users. Moreover, multi-media input/output with HCI should also be developed. Thirdly, at the infrastructure level, we are facing a dilemma: the controllability and learnability. To be specific, if we give users more control of geospatial cyberinfrastructure, the corresponding training work also increase. If we want to keep geospatial cyberinfrastructure easy to learn, we should hide most details about the geospatial cyberinfrastructure. Hot to balance the controllability and learnability is a great challenge in the user-centric design of geospatial cyberinfrastructure.

–cyberinfrastructure

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HCI, Cognition, Systems and Designing Better GIS

Wednesday, March 21st, 2012

Mordechai Haklay and Carolina Tobon provide an interesting overview of the use of GIS by non-experts, with a good focus on how public participation in GIS continues to shape the actual GIS systems in a manner that makes them more accessible and easy to use. In particular, I find their section on the workshops they conducted (582-588) to evaluate the usability of a systems pretty interesting, especially the authors work testing the London Borough of Wandsworth’s new platform. In particular, findings on the need to integrate aerial photos for less sophisticated map users and the need for the system to give feedback to users to confirm they had completed a task struck me as simple, intuitive adjustments many systems leave out. Of course, something as simple as feedback to confirm a task may seem like an obvious part to be included in any system, but I can think of a great many online programs and forms which fail to do this and often leave me wondering if my work/response has been saved.

One of the more interesting aspects of the topic of human-computer interaction, for me, when thinking about it in terms of GIS, includes the way it sits at the intersection of geospatial cognition and geospatial cyberinfrastructure. Perhaps I am biased by my own interests, but this topic pulls these two previous ideas from our class together nicely, as it relies on both to make many of its most salient points. However, one question I had, after reading this paper and discussing cognition in class, remains how do we test geospatial cognition in such a manner that we can apply our findings to better systems design. Often, the field of geospatial cognition seems more obsessed with exploring the ways in which humans understand space and engage in way-finding behavior. I’d be interested in seeing articles/research that really digs into actually applying psychological findings to systems design in a manner that goes beyond the testing these authors have done. I should say they do a nice job, though, of summarizing the theory of how cognitive processes like “issues such as perception, attention, memory, learning and problem solving and [] can influence computer interface and design” (569). Yet I don’t see these concepts applied directly in their testing – perhaps it’s just not covered extensively.

I think it’s only in this way that we can truly bridge the gap between humans and computers. Or is it, humans and networks of computers? Or humans and the cloud? Or humans and the manner in which computers visualize data, represent scale and provide information about the levels of uncertainty? As one might conjecture, the topic of human/computer interaction may be limitless depending on what angle we approach it from.
–ClimateNYC

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Using GCI Without Thinking

Thursday, February 16th, 2012

Chaowei Yang and the other authors of “Geospatial Cyberinfrastructure: Past, Present and Future” believe that the evolution of GCI “will produce platforms for geospatial science domains and communities to better conduct research and development and to better collect data, access data, analyze data, model and simulate phenomena, visualize data and information, and produce knowledge” (264). However, to borrow from Bruno Latour in Science in Action, you can’t help but wonder how much of all of this might just end up being a black box for many disciplines that utilize geospatial data but don’t question how it’s presented and processed. Could this be the quietest revolution in GIS?

The idea of GCIs as black boxes should come as no surprise. Large numbers of people utilize technology that “brings people, information, and computational tools together to perform science” without questioning the underlying “data resources, network protocols, computing platforms and computational services” (267) that help them attain their goals. By using the term black box, I emphasize the meaning Latour intends that it serves a concept or purpose that most people don’t investigate beyond accepting that those in the GCI field have questioned it and made sure it functions.

While I agree with SAH about the exciting potential “a large infrastructure supporting free global geospatial data” holds, I wonder how many people utilizing this network will truly appreciate it. A great deal of people working in academia no doubt. However, users who don’t possess such an academic background or connections to this community might also interact with and contribute to this data source even as GCI remains a black box. While the democratic aspects of this are exciting, I also wonder how we might filter so much data and use it most productively (and ensure its accuracy) in light of the author’s questions about how best to deal with real time data.

-ClimateNYC

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Yang et al and the Politics of Geospatial Cyberinfrastructure

Tuesday, February 14th, 2012

This article gives a comprehensive summary of the functions geospatial cyberinfrastructure (GCI) provide to the public. Yang et al. detail the interlocking/interdependent nature of GCI components that allow the storage, processing, and sharing of vast amounts of data.

            I found that Yang et al. impressed the near-physicality of building and constructing GCI to keep up with our data demands, much like building new roads to handle increased traffic. From the article, it is clear that GCI is the fledgling structure that must support the burden of terabytes of data. The major difference in my view is that GCI is a global, common property unlike roads that only benefit domestic drivers.

            The upshot of the global necessity of GCIs is its inevitable politicization. While the authors stress the scientific and technological benefits of improved GCI, it understresses the political tensions that oppose standardized CIs. Two such examples are science domains eager to stake claim to their own turf and uniqueness (mentioned by the authors), and everyday citizens that have privacy concerns of being monitored and having their information integrated into a large database (see the outrage following every update of Facebook’s policies). These issues pose as significant a challenge as technological problems of cross-integration.

            I truly believe that the politics of turf-staking will fade with the advent of more data sharing made possible with improved GCI. Authoritative scientists just have too much to gain in being able to easily access other fields’ data and advance their own understandings. The general public is even more malleable than purist scientists in this regard and is unlikely to care about what their work is labelled as; their entry into ‘sciences’ is possible due to the flexibility and ease-of-access of open-source online software. The second challenge of privacy concerns is more complicated to me, particularly given the migration of data’s lifecycle onto the Internet (recall that Yang defines lifecycles as getting, validating, documenting, analyzing, and supporting decisions). In the past, data was often only offered online as raw acquired data or as finished products. As more controversial analyses become more visible online due to data-discovery GCIs, this will most likely touch off a firestorm of public debate over the pros and cons of a well-integrated and pervasive GCI.

– Madskiier_JWong

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Developing New Geospatial Cyberinfrastructure with Ontology

Thursday, February 2nd, 2012

Nowadays, geospatial information can be collected with unprecedented speed from multiple sources, including a large body of geosensing systems, historical records, online GIS databases, and so on. On the other hand, user requests for the geospatial information are rapidly growing and the requests always involve distributed heterogeneous data processing. By distributed we mean data are stored or available at different servers, and by heterogeneous we mean data are kept with different format, and both features present great challenges in GIS research. As Kuhn et al. mentioned in their paper in 2001, most traditional geospatial information systems have concentrated on map contents rather than the actual user requirement, which leaves a gap between geospatial cyberinfrastructure and user needs.

Ontology has been proposed to help geospatial information extraction and sharing from the mentioned sources by Kuhn in 2001. The author suggests developing user-oriented GIS instead of map based systems, and using the notion of affordance to establish a hierarchical model of human activities. And their theories have been implemented with the German traffic code project, which has proven the success of utilizing ontology to build the new generation of geospatial cyberinfrastructure.

In 2010, Sieber et al. have built another ontology based geospatial cyberinfrastructure, which incorporates the China Biographical database, the McGill-Harvard-Yenching Library Ming Qing Women’s writing database and China Historical Geographical Information System. This geospatial cyberinfrastructure uses ontology to provide synthesized information about Chinese Women writers in Ming and Qing dynasty, their kinship, publication, and social communities’ information. Utilizing ontology in the design of geospatial cyberinfrastructure, we can enjoy the improvement in spatial knowledge access, discovery and sharing.

 

–cyberinfrastructure

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