Scenario 1: "Learn about a research lab"

Suppose someone wants to know about the UMD HCIL community. He might ask several questions such as, "How many papers have been published at the CHI conference from this lab?", "Have their contributions to the CHI community been growing or shrinking?", "What are the major HCI topics they have been working on?", "Who in this group has the most papers in InfoVis?", and so on. This scenario shows how these questions can be answered using NetLens. As shown in Figure 4(a), users can see there are 80 authors whose affiliations are in Maryland by clicking the "MD" histogram bar in the people overview panel. Figure 4(b) shows those authors are further narrowed down to 63 authors by excluding the institutions other than university (i.e. unselecting Government and Incorporated checkboxes) and also by removing the authors whose affiliation is not University of Maryland from the detail-on-demand panel.

(a) Find authors whose affiliations are in MD

(b) Filter out authors whose affiliations are not UMD


(c) Find papers written by the authors and show distributions


(d) Change paper distribution based on paper topics


(e) Select InfoVis and see the list of papers sorted by # of citations


(f) Find the authors of InfoVis papers and see who published most

Scenario 2:"Determine a good place to go on a sabbatical"

Suppose someone (e.g. Ben Bederson) wants to determine a good place to go on a sabbatical based on analysis of his publications. He can start by finding himself from the people entity window by typing "Bederson" in the free text search box (in Figure 5(a)). Interestingly, there are three Ben Bedersons in the ACM digital libraries due to inconsistent spelling of the author's name. These three names are transferred to the paper entity by setting the between-entity dataflow to "Author to Paper" to show 16 papers written by him (Figure 5(b)). In Figure 5(c), by setting the intra-relationship attribute to "cited by", he found that there are 110 papers that cited his 16 papers. Among 110 citations, 41 of them were published in the ACM CHI conference. Therefore, he saves those 41 papers to his "paper collection" and lets NetLens visualize them in the paper overview panel (Figure 5(d)). Since the histogram shows that the number of citations is growing over time, he decided to choose only the papers published recently (2003 and 2004) by using dynamic filters in the overview window (Figure 5(e)). Now the citations are narrowed down to 15 papers and he set the direction of between-entity dataflow to "Paper to Author" to see the list of authors of the selected 15 papers (Figure 5(f)). He found that there are 57 authors who participated in writing those 15 papers and distributed by nationality to see how many authors are in each country. From the histograms, he found that the UK has the most authors (11 authors) who cited his papers, followed by Sweden (8 authors), France (5 authors), and the Netherlands (5 authors). Therefore, he might eventually decide to go to one of those 4 countries on a sabbatical.

(a) Search "Bederson" from the people entity window

(b) Transfer the names to the paper entity window to see his papers

(c) Found 110 papers that cited his 16 papers

(d) Show 41 CHI papers out of 110 citations in overview panel

(e) Select only the citations that were published recently (2003, 2004)

(f) Transfer papers to Author to show authors by their nationality

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