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      <title-group>
        <article-title>U.S. Congress Prosopographer -A Tool for Prosopographical Research of Legislators</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Goki Miyakita</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Petri Leskinen</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Eero Hyvo¨nen</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>HELDIG - Helsinki Centre for Digital Humanities, University of Helsinki</institution>
          ,
          <country country="FI">Finland</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Research Institute for Digital Media and Content (DMC), Keio University</institution>
          ,
          <country country="JP">Japan</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Semantic Computing Research Group (SeCo), Aalto University</institution>
          ,
          <country country="FI">Finland</country>
        </aff>
      </contrib-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        Person registries and biographies are widely used to document and describe life stories
of historical people, with the aim of getting a better understanding of their personality,
actions, and motivations in history. In biography [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ] the focus is on individual
protagonists, while in prosopography [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] life histories of groups of people are studied in order
to find out some kind of commonness or average in them. The prosopographical
research method [5, p. 47] consists of two steps. First, a target group of people is selected
that share desired characteristics for solving the research question at hand. Second, the
target group is analyzed and compared with other groups to solve the research question.
      </p>
      <p>
        This paper shows how the prosopographical method can be used in practice in
Digital Humanities by presenting a tool and application based on the Linked Data (LD)
paradigm [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. It is shown how faceted search and data visualization tools can be
integrated with a SPARQL endpoint allowing the end user to 1) filter out target groups of
people, and 2) then to study them. A key novelty of this paper is the idea to support
comparing analyses and visualizations based on different target subgroups.
      </p>
      <p>As a use case, a database about the United States Congress Legislators4,5 is used. We
pulled and linked two different datasets: 1) a dataset of the members of the United States
Congress and 2) a dataset based on ICPSR ID6 accompanying Congress numbers7, as
a basis. It contains biographical records of 11 987 persons who served in the U.S.
Congresses from the 1st (1789) to the 115th (2018) one. We converted and extracted the data
(in CSV and YAML format8) into RDF, and developed a SPARQL compliant data
service and an online application named U.S. Congress Prosopographer9 to complement
both quantitative and qualitative inquiry in American political history.
4https://github.com/unitedstates/congress-legislators
5http://k7moa.com
6The Inter-university Consortium for Political and Social Research (ICPSR) ID number
7https://www.senate.gov/reference/Years to Congress.htm
8http://yaml.org/spec/1.2/spec.html
9https://semanticcomputing.github.io/congress-legislators</p>
    </sec>
    <sec id="sec-2">
      <title>Data Model and Linked Data Service</title>
      <p>
        The target RDF data model for representing biographical records is based on the Norssi
biography model [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]. The ontology model representing people and their biographical
information is based on the schema.org vocabulary10. And the data model of schema.org
is extended by additional properties and classes in the domain specific namespace11.
      </p>
      <p>All basic biographical data (family name, gender, given name, etc.) are modeled
using the schema.org namespace, and all the data relating to his or her career are in the
domain namespace. The resources can be linked to external databases or services, such
as DBpedia, Wikidata, Wikipedia, and Twitter, for more information.</p>
      <p>
        The data is available as a Linked Open Data service at the Linked Data Finland
platform12 in an open SPARQL endpoint13 with resolvable URIs, using the W3C Linked
Data publishing principles and best practices [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. For example, the URI http://ldf.fi/
congress/p10079 refers to Harry Truman (1882–1972), and can be used for retrieving
the related RDF data or for Linked Data browsing depending on the need and HTTP
protocol header data used. The data in the service contains altogether ca 830 000 triples,
790 000 in the people graph and 40 000 in the place graph.
3
      </p>
    </sec>
    <sec id="sec-3">
      <title>Supporting Prosopographical Research</title>
      <p>
        As for prosopographical research, U.S. Congress Prosopographer provides a
macroscopic viewpoint in historical time scale following with a microscopic viewpoint of
individual Congress members (Fig. 1). The interface was implemented by extending
SPARQL Faceter [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ], a tool for creating faceted search interfaces on top of a SPARQL
10http://schema.org/docs/schemas.html
11http://ldf.fi/congress/
12http://ldf.fi
13http://ldf.fi/congress/sparql
endpoint. AngularJS14 framework was used to organize linked data together with a
timespan slider15 that is included as a canonical facet. Other filtering facets include
personal attributes, political characteristics, and links to external resources. As shown
in Fig. 1, the interface contains the following four tools for prosopographical research:
a) Multifaceted Search Views The end user is able to customize the facets and
explore the patterns, variations, and uniqueness in the Congress data. Increased
accessibility is supported with intuitive interactive elements, such as simple click and drag.
      </p>
      <p>b) Map visualization To understand the intellectual mobility of Congress
members through the places of their birth and death, Angular Google Maps16 is used in the
visualization to locate, map, and explain historical trends in geographical space.</p>
      <p>c) Two Views of Statistical Visualizations To examine the data through structured
charts, and to provide glanceable overviews of the temporal features, this page generate
statistics in Google Chart diagrams17 based on the extracted filtering results.</p>
      <p>d) Comparing Visualizations These visualizations allow the user to examine the
similarities and differences between the Democratic and Republican parties. In these
visualizations, all functions and visualizations used in a), b), and c) are implemented to
identify and compare the properties of the two different target groups.</p>
      <p>Besides this, every view enables investigation of individual legislator attributes in
depth for biographical investigation.
Use Case Examples The comparison visualizations can be used in different
research studies. For example, it can be shown that during the Reconstruction era from
the 38th through the 45th Congresses (1863–64 to 1877–78) there is a large difference
in the locations of birth and death of the legislators (cf. Fig. 2 LEFT). Most
legislators were born and died in the eastern side. However, the distribution reveals a further
clear tendency during this period: while the Democrats have a longitudinal spreading,
14http://angularjs.org
15https://github.com/angular-slider/angularjs-slider
16http://angular-ui.github.io/angular-google-maps/
17https://developers.google.com/chart/
Republicans remain in the Northeastern megalopolises. Another example is from the
84th through the 89th Congresses (1955–56 to 1965–66) when the federal government
aimed to revitalize cities though funding urban renewal programs.18 During this period
of time, the poor were displaced and suffered from the series of policies. However,
comparing with the overall trend in longevity of service of legislators which continuously
decreases (cf. Fig. 2 RIGHT upper part), there is a wide variation in the longevity
during 1955–66 (cf. Fig. 2 RIGHT bottom part). This indicates that incumbent re-election
rates were extremely high in both parties during this time, despite the fact that the social
situation was very unstable. Hence, through revealing such correlated continuities and
changes, these examples demonstrate how historical patterns correspond to biographical
information and further intertwine with politics, economics, and historical knowledge.
4</p>
    </sec>
    <sec id="sec-4">
      <title>Related Work and Discussion</title>
      <p>U.S. Congress Prosopographer explores different ways to support prosopographical
research. Its different types of visualization for target groups establish context and
maintain orientation while revealing details also about the individuals. This combination of
macro- and microscopic viewpoints offers both qualitative and quantitative
understanding of the biographical and prosopographical aspects of the Congress legislators.</p>
      <p>The idea of combining faceted search and visualizations has been applied, e.g., in
ePistlarium19. However, this tool deals with epistolary data and is not based on Linked
Data. The research of this paper stands unique in providing a comprehensive coverage
of U.S. Congressional biography from its beginning until today through the dynamic
integration of querying and visualizing Linked Data under one single system.</p>
    </sec>
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