A version of this article was presented at the 10th Annual Family History Technology Workshop (FHTW) held on April 28, 2010, in Salt Lake City, Utah, and also was published in the Workshop proceedings—Ed.

A poignant film, the name of which we have forgotten,  shows an elderly Jewish Holocaust survivor, accompanied by her daughter, returning to the village where she had lived as a young girl. As she walks down the streets looking for familiar signs, the woman finally tentatively identifies the site of her family home. The current occupants, themselves an older couple filled with suspicion and hostility, loudly claim that the home has been in their family for generations. The Jewish woman and her daughter eventually walk away sadly, while viewers are left vaguely unsure if the right home actually had been found.

Many people immersed in family history want to know where their people lived, worked, and worshipped. It is part of a link with the family past. Genealogists want to stand where our ancestors stood and walk where they walked; they want to see the ancestral family home, synagogue, and cemetery, or at least where they once stood. No doubt this is particularly true when that past, and the places linked with it, have been defaced, damaged, or destroyed.

The authors believe that the tools of geospatial science provide a powerful means to accomplish these longings. On the ground, these tools can locate the exact places where a great-grandfather lived and where he married his bride. At the computer, these same technologies permit almost the same thing, particularly valuable when travel to distant places is not feasible.

Geospatial Genealogy

The concept geospatial genealogy refers to the linking of traditional genealogical records and databases with the mapping, analysis, and visualization capabilities of online mapping programs such as Google Earth and the more powerful capabilities of geographic information systems (GIS). The term geospatial refers to objects on the Earth and their locational relationships to each other.

Our work fits into a larger schema we call geospatial macrogenealogy. Macrogenealogy, in our view, looks beyond individual family trees by combining data from metrical and other genealogical sources to create what Wagner (2006) calls a “community forest.”¹ It goes beyond family lineages and even distant kinship links to include all persons within a geographical area. Although family links still are vital, macrogenealogy examines a wide range of relationships within a community as they are revealed in the historical records. These include economic, social, cultural, and political relationships and patterns.

Geospatial, at its simplest, refers to the use of maps to record and analyze geographic or spatial patterns. Traditionally, the tools employed were printed maps and perhaps map overlays on transparent paper or plastic. Today the tools of the geospatial analyst focus on computer-based GIS, related tools such as GPS (global positioning system), and remote sensing (air photographs and satellite images).

“Pattern and process” describes one method of discovering or understanding geographical knowledge. The underlying idea is that observed patterns form the basis for studying how the pattern came to be, i.e., the process by which the pattern was formed. This method of inquiry applies both to physical patterns, such as the forms of stream channels, or to cultural patterns, such as the locations of residential and commercial areas within a town. Traditionally, patterns were identified through observations made personally in the field and then transferred to paper maps.

Technological advances over the past 30 years have enabled geographers to combine these methods using GPS to identify locations, remote sensing (satellite images and air photographs) to identify objects visible from overhead, and GIS for electronic mapping and analysis. In the aggregate, these geospatial technologies provide a powerful means for conducting pattern-and-process research.

We view geospatial macrogenealogy as being multiscalar geographically, ranging in scope from the community level (town, village, and shtetl) through the regional level (multiple to numerous communities in a county, raion, or voivodeship) up to the state or national level and beyond. The scale concept is flexible and is best viewed as a continuum from the smallest settlement to the globe rather than as discrete groups segregated by size. In our initial research, we focus on the single town of Rawa Ruska, although we hope to expand our work geographically outward.

Related Research

The past three to five years have seen accelerating interest in applying computer-based mapping technologies to various aspects of family history, and we acknowledge the contributions made by others within this field. In 2008, Moore, et al. described a tool, Family Tree Mapper, that could be used to map the locations of multiple generations from a single family. Similarly, Shular (2009) described the use of geographic information systems (GIS) to map ancestral homesteads, DNA groups, migration trails and key events, surname distributions, and settlement patterns. Dallen Timothy and Jeanne Kay Guelke (2008) published an edited volume exploring a wide range of topics relating to geography and genealogy.

In what follows, we first describe the origins of our research and outline our data sources. Then we develop two threads. The first corresponds to the use of popular online mapping programs (Google Earth, in this case) to visualize and explore ancestral “places,” ranging in scale from individual homes and buildings to entire towns. The second thread focuses on the use of geographic information systems together with genealogical records to explore the life of a village spatially and temporarily through the geographical method of pattern and process.

Study Area

This section describes Rawa Ruska, Ukraine, and the various data sources used to develop the concepts associated with geospatial genealogy. Karen Roekard, one of the authors of this paper, is a descendant of Hasidic Jews who lived in the region of Galicia in what is now Ukraine. Some of her ancestors, including many killed in the Holocaust, lived in the villages of Rawa Ruska and Belz, near the present Ukrainian border with Poland. Following is her abbreviated version of how our collaboration began:

In 2005, I visited Belz and Rawa Ruska, the eastern European towns in which my father was born and raised. On a torrentially rainy day when it was impossible to drive anywhere, I found a tax list from 1812 in the Scientific Library in L’viv. On it were my ancestors’ names, names that my nephews now carry in our generation, and the same house numbers from almost a century later as I had found on the original microfilm upon which the JRI-Poland (Jewish Records Indexing–Poland) records are based.

I realized that Jews in Rawa Ruska often had what we might call “ancestral homes,” house numbers attached to the same family name for 60 to 80 years. This did not include houses where names changed merely through marriage.

In 2006, I returned and spent more than two weeks in the Historical Archive in L’viv, collecting and photographing many other records, including the key to the identification of where each house and building was located in the town, the cadastral map. I was able to follow my ancestors throughout the 19th and early 20th centuries, as they stayed put, changed residences, or expanded throughout the town, as they gave birth, as they died.

I became obsessed with the idea of seeing where every Jewish resident of 1812 and 1854 had lived. I enlarged the maps and by hand wrote in the names of every Jewish family. The outlines of the old Jewish neighborhood became obvious as did the fact that, while not what we would call “integrated,” the Christian and Jewish residents of the town were not segregated either.

In June 2008, while participating as an auditor in the Silberman seminar at the U.S. Holocaust Memorial Museum, I showed my maps to University of Kansas Geography Professor Stephen Egbert. We joined forces to see what might be learned from combining genealogically relevant material with the technology of the geospatial scientists, all viewed through the lens of geography, of “place.”

Data Sources

The cadastral map is the key to our research (Figure 1). Cadastral maps are maps of property ownership. They are used to show, at a minimum, the boundaries and ownership

of real property (real estate) parcels within a given jurisdiction such as a city, county, or parish. Cadastral maps may also include additional information such as unique identifying lot or house numbers, tax values, the locations of structures and other improvements, or adjacent street names.

The cadastral map would be meaningless, however, without other records that provide the “house number link” to the cadastral map. Following are the primary record sources for our project.

• Contractual Material. These records—the Tabula Register Collection—are the original town books into which people copied the contracts they had undertaken—business, real estate, marriage, and probate—thus legalizing the contracts. In Rawa Ruska and the rest of Galicia, these books were kept from approximately 1772 to about 1882. Today the records are stored in the Central State Historical Archives in L’viv.
• Books of Contracts. The contracts themselves have names of all the parties involved and often (especially in the real estate contracts) their house numbers; parents, spouse, and/or children’s names; and location of their property by identification of neighbors and geographic landmarks.
• Index Books of Real Estate Transactions. These books are indexes of the real estate books and include names of parties involved; former names; house numbers; old house numbers if changed; parents, spouse, and/or children’s names.
• Property Owners/Taxpayer Lists. These records hold listings of people who owned property and/or paid taxes within Rawa Ruska.
• 1812 Taxpayer’s List. This assessment divided the community into two categories, Christian or Jewish, and created separate lists for each. It provides name of taxpayer; house number for which they are paying taxes; and amounts paid on house, grounds, and farm animals. The original records are held in the Scientific Library in L’viv.
• 1854 Property Owner’s List. This listing merged the Ukrainian, Polish, and Jewish communities into one list, alphabetical, by family name. It includes name, affiliation, and all properties owned by each individual (including house numbers). The original records are held in the Central State Historical Archives in L’viv.
• 1934 Jewish Taxpayer’s List. This list has no house numbers, only Jewish names and only the name and the amount of taxes assessed in 1932, 1933, and 1934. The originals of these records are in the Central State Historical Archives in L’viv. A legible microfilmed copy is available at the Central Archives for the History of the Jewish People in Jerusalem.
• Vital Records. These records cover legally acknowledged or sanctioned life cycle events for which records were kept—births, marriages, deaths, and divorces. In Rawa Ruska, the events are registered by religious affiliation: Roman Catholic (seemingly Polish), Eastern Catholic (seemingly Ukrainian—and for a period of time, written in Ukrainian), and Jewish.

Jewish records, though representing a population that was murdered and that no longer has living representation in the town, are withheld by the authorities under Ukraine’s 100-year privacy laws and are available only through the first decade of the 20th century. Microfilmed copies of Christian birth, death, and marriage records are available from the LDS (Mormon) microfilm database. Limited information from the Jewish records (but not house numbers) is available online at <www.JewishGen. org>. The original records are housed in the Archiwum Glowne Akt Dawnych (AGAD), The Central Archives of Historical Records in Warsaw.

• Content of Vital Records. Researchers may assume that birth records always include the baby’s and mother’s name and date of birth (plus baptism or circumcision and “legitimacy”); usually name of father, midwife, at least one set of grandparents and witnesses to registration; sometimes occupations and house numbers. Christian rec­ords all have “station,” a concept in the life of the community based somewhat on occupation, and house number. Starting in the 20th century, Jewish birth records consistently included house numbers.

Death records usually provide date of death, name of deceased, age, cause, and sometimes names of parents and/or spouse. Christian records usually supply house numbers; Jewish records are mixed. Christian marriage records generally have at least the date, partners and their parents’ names, religion of each partner, witness’ name, and house numbers. Jewish marriage records for Rawa Ruska are missing.

Using Google Earth and a Cadastral Map to Explore Rawa Ruska

Most readers have been exposed to the wonders of Google Earth, its eye-in-the-sky views letting us zoom in on cities, towns, and natural wonders in exotic places as easily as we zoom in on our own homes. Google Earth is continuously upgrading the detail of its air photographs and satellite images, and recently added detailed satellite images of many Polish and Ukrainian towns and villages, including Rawa Ruska.

The authors have begun to explore the use of Google Earth as a way to overlay 19th-century cadastral maps of Galician towns onto those of present-day satellite images. This is accomplished by adding a photograph of a cadastral map in Google Earth as an “image overlay.” Move and stretch the map into place using features seen on both the map and the satellite image as reference points.² These might be road intersections or large permanent buildings such as churches. Use any surveyed map—it need not be a cadastral map.

Once a map is positioned correctly, use a slider to make the map appear transparent or opaque, or anything in between. This shows where buildings and roads have disappeared, where they have been added or changed, and where they still exist. The image overlay may be saved to one’s Google Earth Places and can be shared with others.

Figure 2 illustrates the effect created by overlaying a cadastral map on a satellite image in Google Earth. It can readily be seen that the buildings on the town square and the synagogue (squares) no longer exist. The two Christian churches, Saint Josef and Saint Maria (circles), still stand. Further examination reveals that many residential structures, especially around the town center, have disappeared. In some cases, new structures have been built; in others cases, the land is vacant.³

In some cases where a building has disappeared, it is possible to zoom in to Google Earth and see the outlines of the building’s foundation, even after it has long disappeared. Such outlines, which may be from stones or cement rubble or perhaps from vegetation growing poorly in the shallow soil over the former foundation, are relict features from bygone eras that provide visual cues and reminders of what once was. In other cases, no traces exist except the virtual or “ghost” features seen on old cadastral maps.

Visual exploration of an ancestral village like Rawa Ruska is only the beginning, of course. By cross-referencing the house numbers found in vital records with the corresponding numbers on the cadastral map it is possible to identify geographic coordinates for specific homes, buildings, and other locations. These can then be uploaded to a GPS that can guide the genealogical tourist to the exact spot (usually within a few meters) of where the building stands today—or, as in the case of the destroyed synagogue in Rawa Ruska, where it once stood. Harking back to the video of the Holocaust survivor searching for her ancestral home, with Google Earth and a GPS she (and we) might have known for certain where her home stood.

A further dimension can be added once the original site of interest has been located on the ground. One can take a photograph of the location—a grave marker in a cemetery, for example—and “geotag” the photograph by adding the geographic coordinates (i.e., the latitude and longitude) to

Figure 2. Screen captures of Rawa Ruska from Google Earth. The picture on the left is a satellite image of Rawa Ruska as it appears today. On the right, the 1854 cadastral map has been overlaid on the modern satellite image as a midway transparency. Refer to text for further explanation.

the digital photo file. This can be done manually using any one of several free or inexpensive pieces of geotagging software (e.g., GeoSetter, RoboGeo, GeoPhoto, or others) or, if you have a camera that has a GPS (including many smart phones), you can geotag your photos automatically in the field each time you take a picture. Geotagged photographs may easily be added to Google Earth or similar programs as an additional and important way of visualizing an ancestral village or home. It is relatively simple to modify a photograph’s pop-up information window in Google Earth to include genealogical information about the former occupants of a home, for example.

GIS, Geospatial Genealogy, and Rawa Ruska

At a superficial level, GIS sometimes is thought of as computerized map making. In reality, the capabilities of GIS go far beyond the ability to use computer programs to draw maps. A GIS consists of computer hardware (normally a high-end PC or “workstation”), specialized GIS software, and geographic (“geospatial”) data. According to one definition, “A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information.” (ESRI, 2010)

The roots of GIS go back to the 1950s and 1960s, when government agencies and university laboratories began to harness the power of computers to assist in collecting, storing, and mapping complex data sets for censuses, land use planning, and utilities management. (Longley et al., 2005) With ever-increasing computer hardware capabilities, especially in data storage, processor speeds, and graphics, coupled with developments in spatial analytical algorithms, GIS has become a powerful analysis and management tool. Today, virtually all levels of government, from municipal to national, have GIS departments, sections, or “shops” to manage and communicate their geospatial data. GIS also is used extensively in the private sector for applications ranging from route planning to analyzing potential locations for warehouses or retail outlets. GIS is a multi-billion dollar industry, complete with specialized university programs, textbooks, and annual industry conferences.

GIS Databases

In a GIS database, the key piece of information is location, whether it be latitude and longitude or other map coordinate systems. Everything else in the GIS database is tied to the location. The “everything else” might include street address, name of the property owner, number of occupants of the home, value of the property, size of the home on the property, and so on. These pieces of information are called “attributes” in GIS. Conceptually, a GIS database may be thought of as consisting of a series of maps or map layers stacked on top of each other.

Because of the underlying database structure, GIS is much more than the computer equivalent of a paper map. In particular, GIS combines the power of database queries with graphic presentations. For example, a GIS analyst might say, “Show me all the houses within the county boundaries that have an assessed value of less than $250,000 that are located more than 300 feet from a fire hydrant.” In this example, we assume that map databases already have been created for county boundaries, assessed property values, and the locations of fire hydrants. The result of the query can be displayed on a map or in the tabular form familiar to database or spreadsheet users. In only a matter of seconds, the query may be changed to another set

of variables and parameters. Because of the ability to access underlying databases and display the results graphically, GIS maps are sometimes referred to as “smart maps.”

Creating a GIS Database of Rawa Ruska

In our case, the key GIS map is an 1854 cadastral map of Rawa Ruska that shows the locations of houses and buildings along with their numbers (Figure 1). These building numbers are included in some of our other record sources and enable us to tie various genealogical attributes to the houses through time.

The Rawa Ruska cadastral map was photographed in the archives at L’viv using a digital camera. To prepare the map for inclusion in a GIS, the photograph was used as a visual backdrop in a GIS software program and each of the buildings was traced using the mouse cursor, a process called screen digitizing. Creation of the digital map is one of the most important parts of creating the GIS—without the digital map, there is no GIS and no analysis. The outlines of Rawa Ruska’s buildings and houses shown in Figure 3 formed the base map layer for our GIS—it was now ready for attributes such as house type (brick or wood), tax value, owner’s name, religion of owner, and others.

Attributes were entered and organized using an Excel spreadsheet. (We also could have used a database program or entered the attributes directly into the GIS program’s own database.) The spreadsheet was then imported into the GIS database. This was done by matching the house numbers in the GIS database to the same house numbers in the corresponding column on the spreadsheet. With the base map and attributes in place, we were now ready to perform some basic queries to explore residential patterns in Rawa Ruska.

Initial GIS Results

At the simplest level, a query can be made to discover information about each house or building. For example, by using the mouse to click on a particular house, an attribute window will pop up showing all the data attributes for that house. In Figure 4, house number 40 has been selected. The attribute database table shows that the owner in 1812 was Hertz Baran, who was Jewish. His house was constructed of wood. Conversely, we could have opened the attribute database table from which we selected a house number or owner and seen the house highlighted on the map.

In a somewhat more complex fashion, a query can be constructed that will highlight all the houses and buildings that fall into a particular category. For example, the GIS can show all houses occupied by Jews in 1854 (Figure 5). Results of the query illustrate the geographic (spatial) patterns of Jewish residences in Rawa Ruska in that year. Not surprisingly, Jews lived in close proximity to each other in several clusters or neighborhoods. Also not surprisingly, few Jewish residences are near the two Christian churches, Saint Joseph and Saint Mary (Sct. Josef, Sct. Maria on the maps). Most Jews were living in wooden rather than brick structures, likely a reflection of the overall poverty of the Jewish community in a relative sense. (This judgment was easily made by visual means, but we also could have performed a query that would specifically show the number of Jewish homes that were brick or wood.) We further see that in 1854 few Jews live in residences facing the town square and apparently not a single residential area was restricted only to Jews. In fact, Jewish homes are found in most parts of the town itself as well as in the surrounding rural area.

Future Plans/Dreams

When the authors began their research, they envisioned limited goals—maps of individual residences or perhaps all residences by religion or ethnicity for a single year, for example, such as those seen from our initial results. Those goals have begun to expand with increased understanding of the potential power of combining geospatial technologies and genealogical databases. Following is a sample of goals for future development:

Figure 5. Homes (shown in black) listed as owned by Jews in Rawa Ruska in 1854.

• Add and link other records from Rawa Ruska to the geographic database. In some cases, these may be Christian vital records.
• With the extended database, explore further the spatial patterns in Rawa Ruska as the basis for understanding the processes that led to the patterns in the first place. We know, for example, that by 1939 Jews lived in homes surrounding the town square. When and how (and why) did that happen?
• Expand the analysis to surrounding settlements in Eastern Galicia.
• Develop the interface between the disparate database worlds of genealogy and GIS. This is perhaps the most important problem facing us. To this point, we have primarily used “brute force” methods to link genealogical and GIS databases. We need to identify and develop more elegant solutions that will permit broader application of these technologies by more family history researchers.
• Finally, we wish to publicize widely this effort to genealogists working in other realms, both topically and regionally to build further capabilities in visualizing our ancestral lands and homes.³

References

Carlson, K.T. 2001. A Sto:lo Coast Salish Historical Atlas. Seattle: University of Washington Press.

ESRI, 2010. GIS.com: the Guide to Geographic Information Systems. <www.gis.com/content/what-gis> (Last accessed January 6, 2010.)

Guelke, J.K. and Timothy, D.J. 2008. “Locating Personal Pasts, An Introduction,” in Timothy, D. and Guelke, J.K. (eds.). Geography and Genealogy: Locating Personal Pasts. Burlington, VT: Ashgate , 2008.

Kain, R.J.P, and Baigent, E. The Cadastral Map in the Service of the State. Chicago: University of Chicago Press. 1992. (See, especially Chapter 5: The Austrian Habsburg Lands, with the Principality of Piedmont, pp. 175-204.)

Kashuba, M. 2008. “The Unfolding Tale of Using Maps in Genealogical Research” in Timothy, D. and Guelke, J.K. (eds.). Geography and Genealogy: Locating Personal Pasts.

Lenius, B.J. 2005. Cadastral Land Surveys and Maps for Galicia, Austria. East European Genealogist Spring 2005, 13(3):10-15.

Longley, Paul A., Goodchild, Michael F., Maguire, David J., and David W. Rhind. Geographical Information Systems and Science. Chichester, England: John Wiley and Sons, 2005.

Moore, M., Hallstrom, Hess, C., Fryer, C., Caswell, D., Benner, M., Butterfield, J. and Helps, R. “Geospatial Family History Research: Designing a Research Tool.” Proceedings, Family History Technology Workshop. Brigham Young University, Provo, Utah, 2008.

Ruvane, M.B. and Dobbs, G.R. 2008. “Genealogy, Historical Geography, and GIS: Parcel Mapping, Information Synergies, and Collaborative Opportunities” in Timothy, D. and Guelke, J.K. (eds.). 2008. Geography and Genealogy: Locating Personal Pasts. Burlington, Vermont.

Shular, M.D. “Turning Genealogists onto GIS.” Journal of Map and Geography Libraries 5:55-71, 2009.

Vogel, C.G. and Stroh, Y.N. “Constructing a Town-Wide Genealogy: Jewish Mattersdorf, Hungary, 1698-1939.” AVOTAYNU The International Review of Jewish Genealogy, Vol. XXIII, No. 1, Spring 2007: 30-39.

Wagner, H. Daniel. “Genealogy as an Academic Discipline.” AVOTAYNU, The International Review of Jewish Genealogy, Vol. XXII, No. 1, Spring 2006.

Notes

1. Our view of macrogenealogy varies somewhat from Wagner, who views macrogenealogy or “global genealogy” as involving “issues and tools relevant to genealogy as a whole.” Our geospatial genealogical research most likely would fall under the heading of “confined microgenealogy” in his taxonomy. Despite differences in terminology, we are indebted to him for describing his thought-provoking vision of the scope of academic genealogical research.
2. The tools in Google Earth for matching cadastral or other maps to the underlying satellite imagery are essentially crude tools for performing a procedure known as image rectification. Ideally, image rectification would be done using image processing software, where numerous control points and mathematical models are used to “rubber sheet” an image to fit another image that is already correctly matched to the earth’s geographic coordinate system.
3. The authors expect to overcome the limitation imposed in viewing the visuals in black & white by putting up a full-color/complete graphics website devoted to geospatial genealogy by mid-July 2010 at <www.geospatialgenealogy.org>.