What is research (1)

This abstract tells me a lot of stories about itself. Here I want to discuss two stories about it.
It has demonstrated an excellent job of promoting and abstracting itself to a higher level by playing with words. The work this abstract has done is merely proposing a new land classification system using big data. Essentially, the contribution in this abstract could be nothing new to the scientific literature because a lot of similar work have been done. For example, Soto and Frías-Martínez (2011) conducted an land use identification using mobile phone data, a typical kind of big data. So does Toole et al. (2012). Urban structure, another term which is the other side of urban land use in my opinion, has been also analyzed by many scholars (Long and Liu, 2013; Yuan et al., 2013). But this abstract, by using some philosophical terms in this field, indicated its ‘novelty’ in a very smart way. Let us find that out one by one.
In this abstract, the tile used a term ‘typology’, instead of using the more mediocre term ‘classification’, giving the readers a epistemology-level sense of academic research. In the end of first paragraph, it explained its difference with conventional land use classification which is unit of analysis and the continuity of time and space. Unit of analysis, I suppose, means the basic units this abstract identified are more homogeneous in terms of some characteristics. Thus, as the big data has the time dimension, the new classification using big data did improve its temporal and spatial continuity. All in all, this abstract did not contribute so much as it claimed itself; what it did contribute is just to summarize the implications of this big-data-based land use classification method.
Also, this abstract showed its capability of hiding itself from being probed into. Through the whole abstract, it didn’t say a single word about operationalization and how it is going to do. I guess the author could possibly deleted this operation part which was supposed to be in the second paragraph in this abstract. But, we can not criticize it too much because it is a precaution measure in academic communication scenarios, especially in an academic conference like AAG several thousands of people attended.

Reference
Soto, V., & Frías-Martínez, E. (2011). Automated land use identification using cell-phone records. Paper presented at the Proceedings of the 3rd ACM international workshop on MobiArch.
Toole, J. L., Ulm, M., González, M. C., & Bauer, D. (2012). Inferring land use from mobile phone activity. Paper presented at the Proceedings of the ACM SIGKDD International Workshop on Urban Computing.
Long, Y., & Liu, X. (2013). Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest.
Yuan, J., Zheng, Y., & Xie, X. (2012). Discovering Regions of Different Functions in a City Using Human Mobility and POIs. Paper presented at the ACM KDD, Beijing, China.

Attached Abstract
Abstract Title: Redefining the Typology of Land Use with Big Data
Author(s): *** - Massachusetts Institute of Technology
Abstract: According to the Wall Street Journal, "check in" was the 12th most popular word of 2010.  The underlying picture of this phenomenon is that information sharing and location based services have been so easy in the city. Compared with conventional land use data, these types of big data might tell us much about how urban land is being used in a more dynamic and human-respected way. However there has been few researches focusing on the new opportunities brought by big data onto urban land use classification—the basic "language" of urban geography and planning. In this context, this paper builds a new theoretical framework for urban land use description, and redefines the concept of "land use" in multiple scales of urban geographies. Compared with the conventional land use classification, this new framework is more specific on the key issues of urban geography, such as the unit of analysis and the continuity of time and space.
The new framework of land use typology will challenge our conventional view on land use.  Its implication could include but not only: 1) Change the way that land use is defined in the field of urban planning; 2) Develop land use as a language to describe urban activities and settlement; 3) Connect land use typology with broader fields such as travel behavior/transportation analysis, energy consumption of land use, density and urban form and so on.
Keywords: Urban land use; land use categorization; location based big data