Search (10 results, page 1 of 1)

0.078474775 = product of:
  0.15694955 = sum of:
    0.032486375 = weight(_text_:library in 1289) [ClassicSimilarity], result of:
      0.032486375 = score(doc=1289,freq=4.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.24650425 = fieldWeight in 1289, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.046875 = fieldNorm(doc=1289)
    0.12446317 = sum of:
      0.083718576 = weight(_text_:project in 1289) [ClassicSimilarity], result of:
        0.083718576 = score(doc=1289,freq=4.0), product of:
          0.21156175 = queryWeight, product of:
            4.220981 = idf(docFreq=1764, maxDocs=44218)
            0.050121464 = queryNorm
          0.39571697 = fieldWeight in 1289, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.220981 = idf(docFreq=1764, maxDocs=44218)
            0.046875 = fieldNorm(doc=1289)
      0.0407446 = weight(_text_:22 in 1289) [ClassicSimilarity], result of:
        0.0407446 = score(doc=1289,freq=2.0), product of:
          0.17551683 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.050121464 = queryNorm
          0.23214069 = fieldWeight in 1289, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=1289)
  0.5 = coord(2/4)

Abstract

QVIZ will research and create a framework for visualizing and querying archival resources by a time-space interface based on maps and emergent knowledge structures. The framework will also integrate social software, such as wikis, in order to utilize knowledge in existing and new communities of practice. QVIZ will lead to improved information sharing and knowledge creation, easier access to information in a user-adapted context and innovative ways of exploring and visualizing materials over time, between countries and other administrative units. The common European framework for sharing and accessing archival information provided by the QVIZ project will open a considerably larger commercial market based on archival materials as well as a richer understanding of European history.

Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

0.07571602 = product of:
  0.10095469 = sum of:
    0.051698197 = weight(_text_:digital in 1202) [ClassicSimilarity], result of:
      0.051698197 = score(doc=1202,freq=8.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.26148933 = fieldWeight in 1202, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
    0.034457 = weight(_text_:library in 1202) [ClassicSimilarity], result of:
      0.034457 = score(doc=1202,freq=18.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.2614572 = fieldWeight in 1202, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
    0.014799493 = product of:
      0.029598987 = sum of:
        0.029598987 = weight(_text_:project in 1202) [ClassicSimilarity], result of:
          0.029598987 = score(doc=1202,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.13990708 = fieldWeight in 1202, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.0234375 = fieldNorm(doc=1202)
      0.5 = coord(1/2)
  0.75 = coord(3/4)

Abstract

The concept of c-space is proposed as a visualization schema relating containers of content to cataloging surrogates and classification structures. Possible applications of keyword vector clusters within c-space could include improved retrieval rates through the use of captioning within visual hierarchies, tracings of semantic bleeding among subclasses, and access to buried knowledge within subject-neutral publication containers. The Scholastica Project is described as one example, following a tradition of research dating back to the 1980's. Preliminary focus group assessment indicates that this type of classification rendering may offer digital library searchers enriched entry strategies and an expanded range of re-entry vocabularies. Those of us who work in traditional libraries typically assume that our systems of classification: Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC), are descriptive rather than prescriptive. In other words, LCC classes and subclasses approximate natural groupings of texts that reflect an underlying order of knowledge, rather than arbitrary categories prescribed by librarians to facilitate efficient shelving. Philosophical support for this assumption has traditionally been found in a number of places, from the archetypal tree of knowledge, to Aristotelian categories, to the concept of discursive formations proposed by Michel Foucault. Gary P. Radford has elegantly described an encounter with Foucault's discursive formations in the traditional library setting: "Just by looking at the titles on the spines, you can see how the books cluster together...You can identify those books that seem to form the heart of the discursive formation and those books that reside on the margins. Moving along the shelves, you see those books that tend to bleed over into other classifications and that straddle multiple discursive formations. You can physically and sensually experience...those points that feel like state borders or national boundaries, those points where one subject ends and another begins, or those magical places where one subject has morphed into another..."
But what happens to this awareness in a digital library? Can discursive formations be represented in cyberspace, perhaps through diagrams in a visualization interface? And would such a schema be helpful to a digital library user? To approach this question, it is worth taking a moment to reconsider what Radford is looking at. First, he looks at titles to see how the books cluster. To illustrate, I scanned one hundred books on the shelves of a college library under subclass HT 101-395, defined by the LCC subclass caption as Urban groups. The City. Urban sociology. Of the first 100 titles in this sequence, fifty included the word "urban" or variants (e.g. "urbanization"). Another thirty-five used the word "city" or variants. These keywords appear to mark their titles as the heart of this discursive formation. The scattering of titles not using "urban" or "city" used related terms such as "town," "community," or in one case "skyscrapers." So we immediately see some empirical correlation between keywords and classification. But we also see a problem with the commonly used search technique of title-keyword. A student interested in urban studies will want to know about this entire subclass, and may wish to browse every title available therein. A title-keyword search on "urban" will retrieve only half of the titles, while a search on "city" will retrieve just over a third. There will be no overlap, since no titles in this sample contain both words. The only place where both words appear in a common string is in the LCC subclass caption, but captions are not typically indexed in library Online Public Access Catalogs (OPACs). In a traditional library, this problem is mitigated when the student goes to the shelf looking for any one of the books and suddenly discovers a much wider selection than the keyword search had led him to expect. But in a digital library, the issue of non-retrieval can be more problematic, as studies have indicated. Micco and Popp reported that, in a study funded partly by the U.S. Department of Education, 65 of 73 unskilled users searching for material on U.S./Soviet foreign relations found some material but never realized they had missed a large percentage of what was in the database.

0.042943195 = product of:
  0.08588639 = sum of:
    0.043081827 = weight(_text_:digital in 3870) [ClassicSimilarity], result of:
      0.043081827 = score(doc=3870,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.21790776 = fieldWeight in 3870, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3870)
    0.042804558 = weight(_text_:library in 3870) [ClassicSimilarity], result of:
      0.042804558 = score(doc=3870,freq=10.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.32479787 = fieldWeight in 3870, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3870)
  0.5 = coord(2/4)

Abstract

Data from multiple knowledge organization systems are combined to provide a global overview of the content holdings of a small personal library. Subject headings and classification data are used to effectively map the combined book and topic space of the library. While harvested and manipulated by hand, the work reveals issues and potential solutions when using automated techniques to produce topic maps of much larger libraries. The small library visualized consists of the thirty-nine, digital, English language books found in the Osama Bin Laden (OBL) compound in Abbottabad, Pakistan upon his death. As this list of books has garnered considerable media attention, it is worth providing a visual overview of the subject content of these books - some of which is not readily apparent from the titles. Metadata from subject headings and classification numbers was combined to create book-subject maps. Tree maps of the classification data were also produced. The books contain 328 subject headings. In order to enhance the base map with meaningful thematic overlay, library holding count data was also harvested (and aggregated from duplicates). This additional data revealed the relative scarcity or popularity of individual books.

0.03111944 = product of:
  0.06223888 = sum of:
    0.036556147 = weight(_text_:digital in 1197) [ClassicSimilarity], result of:
      0.036556147 = score(doc=1197,freq=4.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.18490088 = fieldWeight in 1197, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1197)
    0.025682734 = weight(_text_:library in 1197) [ClassicSimilarity], result of:
      0.025682734 = score(doc=1197,freq=10.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.19487871 = fieldWeight in 1197, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1197)
  0.5 = coord(2/4)

Abstract

User interfaces for digital information discovery often require users to click around and read a lot of text in order to find the text they want to read-a process that is often frustrating and tedious. This is exacerbated because of the limited amount of text that can be displayed on a computer screen. To improve the user experience of computer mediated information discovery, information visualization techniques are applied to the digital library context, while retaining traditional information organization concepts. In this article, the "virtual (book) spine" and the virtual spine viewer are introduced. The virtual spine viewer is an application which allows users to visually explore large information spaces or collections while also allowing users to hone in on individual resources of interest. The virtual spine viewer introduced here is an alpha prototype, presented to promote discussion and further work. Information discovery changed radically with the introduction of computerized library access catalogs, the World Wide Web and its search engines, and online bookstores. Yet few instances of these technologies provide a user experience analogous to walking among well-organized, well-stocked bookshelves-which many people find useful as well as pleasurable. To put it another way, many of us have heard or voiced complaints about the paucity of "online browsing"-but what does this really mean? In traditional information spaces such as libraries, often we can move freely among the books and other resources. When we walk among organized, labeled bookshelves, we get a sense of the information space-we take in clues, perhaps unconsciously, as to the scope of the collection, the currency of resources, the frequency of their use, etc. We also enjoy unexpected discoveries such as finding an interesting resource because library staff deliberately located it near similar resources, or because it was miss-shelved, or because we saw it on a bookshelf on the way to the water fountain.
When our experience of information discovery is mediated by a computer, we neither move ourselves nor the monitor. We have only the computer's monitor to view, and the keyboard and/or mouse to manipulate what is displayed there. Computer interfaces often reduce our ability to get a sense of the contents of a library: we don't perceive the scope of the library: its breadth, (the quantity of materials/information), its density (how full the shelves are, how thorough the collection is for individual topics), or the general audience for the materials (e.g., whether the materials are appropriate for middle school students, college professors, etc.). Additionally, many computer interfaces for information discovery require users to scroll through long lists, to click numerous navigational links and to read a lot of text to find the exact text they want to read. Text features of resources are almost always presented alphabetically, and the number of items in these alphabetical lists sometimes can be very long. Alphabetical ordering is certainly an improvement over no ordering, but it generally has no bearing on features with an inherent non-alphabetical ordering (e.g., dates of historical events), nor does it necessarily group similar items together. Alphabetical ordering of resources is analogous to one of the most familiar complaints about dictionaries: sometimes you need to know how to spell a word in order to look up its correct spelling in the dictionary. Some have used technology to replicate the appearance of physical libraries, presenting rooms of bookcases and shelves of book spines in virtual 3D environments. This approach presents a problem, as few book spines can be displayed legibly on a monitor screen. This article examines the role of book spines, call numbers, and other traditional organizational and information discovery concepts, and integrates this knowledge with information visualization techniques to show how computers and monitors can meet or exceed similar information discovery methods. The goal is to tap the unique potentials of current information visualization approaches in order to improve information discovery, offer new services, and most important of all, improve user satisfaction. We need to capitalize on what computers do well while bearing in mind their limitations. The intent is to design GUIs to optimize utility and provide a positive experience for the user.

0.029829983 = product of:
  0.059659965 = sum of:
    0.043081827 = weight(_text_:digital in 1211) [ClassicSimilarity], result of:
      0.043081827 = score(doc=1211,freq=8.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.21790776 = fieldWeight in 1211, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
    0.016578136 = weight(_text_:library in 1211) [ClassicSimilarity], result of:
      0.016578136 = score(doc=1211,freq=6.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.12579368 = fieldWeight in 1211, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
  0.5 = coord(2/4)

Abstract

In this article we present a method for retrieving documents from a digital library through a visual interface based on automatically generated concepts. We used a vocabulary generation algorithm to generate a set of concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. An online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test the utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks. Over the past few years, the volume of information available through the World Wide Web has been expanding exponentially. Never has so much information been so readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over networks have made it hard for users to sift through and find relevant information. To deal with this problem, information retrieval (IR) techniques have gained more intensive attention from both industrial and academic researchers. Numerous IR techniques have been developed to help deal with the information overload problem. These techniques concentrate on mathematical models and algorithms for retrieval. Popular IR models such as the Boolean model, the vector-space model, the probabilistic model and their variants are well established.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

0.0076571116 = product of:
  0.030628446 = sum of:
    0.030628446 = weight(_text_:library in 580) [ClassicSimilarity], result of:
      0.030628446 = score(doc=580,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.23240642 = fieldWeight in 580, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0625 = fieldNorm(doc=580)
  0.25 = coord(1/4)

0.0073997467 = product of:
  0.029598987 = sum of:
    0.029598987 = product of:
      0.059197973 = sum of:
        0.059197973 = weight(_text_:project in 2906) [ClassicSimilarity], result of:
          0.059197973 = score(doc=2906,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.27981415 = fieldWeight in 2906, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.046875 = fieldNorm(doc=2906)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.

0.0066312538 = product of:
  0.026525015 = sum of:
    0.026525015 = weight(_text_:library in 2547) [ClassicSimilarity], result of:
      0.026525015 = score(doc=2547,freq=6.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.20126988 = fieldWeight in 2547, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.03125 = fieldNorm(doc=2547)
  0.25 = coord(1/4)

Abstract

The discovery service (a search engine and service called WILBERT) used at our library at the Technical University of Applied Sciences Wildau (TUAS Wildau) is comprised of more than 8 million items. If we were to record all licensed publications in this tool to a higher level of articles, including their bibliographic records and full texts, we would have a holding estimated at a hundred million documents. A lot of features, such as ranking, autocompletion, multi-faceted classification, refining opportunities reduce the number of hits. However, it is not enough to give intuitive support for a systematic overview of topics related to documents in the library. John Naisbitt once said: "We are drowning in information, but starving for knowledge." This quote is still very true today. Two years ago, we started to develop micro thesauri for MINT topics in order to develop an advanced indexing of the library stock. We use iQvoc as a vocabulary management system to create the thesaurus. It provides an easy-to-use browser interface that builds a SKOS thesaurus in the background. The purpose of this is to integrate the thesauri in WILBERT in order to offer a better subject-related search. This approach especially supports first-year students by giving them the possibility to browse through a hierarchical alignment of a subject, for instance, logistics or computer science, and thereby discover how the terms are related. It also supports the students with an insight into established abbreviations and alternative labels. Students at the TUAS Wildau were involved in the developmental process of the software regarding the interface and functionality of iQvoc. The first steps have been taken and involve the inclusion of 3000 terms in our discovery tool WILBERT.

0.0061664553 = product of:
  0.024665821 = sum of:
    0.024665821 = product of:
      0.049331643 = sum of:
        0.049331643 = weight(_text_:project in 4837) [ClassicSimilarity], result of:
          0.049331643 = score(doc=4837,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.23317845 = fieldWeight in 4837, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4837)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This "position paper" also prepares to demonstrate our hypothesis by an "iconic social tagging" experiment which is to be accomplished in 2011 with UTT students. We describe the "socio semantic web" information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust "icons systems".

0.0025465374 = product of:
  0.01018615 = sum of:
    0.01018615 = product of:
      0.0203723 = sum of:
        0.0203723 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
          0.0203723 = score(doc=3035,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.116070345 = fieldWeight in 3035, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0234375 = fieldNorm(doc=3035)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Content

As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.