Networking the Topics in an Ambassador’s Letters (Part 3)

My dry run on Palladio and RAW went well, generally. I have my data formatted well for the use of the graph function in Palladio and all of the functions in RAW. It is amazing how easily one can see certain information when turned into a visualization.
Mahomet Bassahenri iii1579-12-081580-01-091580-03-17catherine de medici1579-12-08sinan bassacatherine de medici1579-12-241580-02-06henri iii1579-12-24Wallachiahenri iii1579-12-08Semisi Bassahenri iii1579-12-081580-02-12catherine de medici1579-12-081580-01-26Englandhenri iii1579-12-081580-03-17Agmar premier viziercatherine de medici1579-12-08vayvode de Bogdaniacatherine de medici1579-12-08Alepcatherine de medici1579-12-08Rustan Bassacatherine de medici1579-12-08la sultane femmecatherine de medici1579-12-081579-12-24osman bassacatherine de medici1579-12-08tartarescatherine de medici1579-12-08henri iii1580-03-03roy d’espagnehenri iii1579-12-241580-01-09arabiehenri iii1579-12-24mustafa bassahenri iii1579-12-241580-03-17catherine de medici1580-01-26Persehenri iii1579-12-24sr. batoryhenri iii1579-12-24transylvaniahenri iii1579-12-24aymar bassahenri iii1579-12-24catherine de medici1579-12-24Joseph Mickeshenri iii1579-12-08greece catherine de medici1579-12-24Agacatherine de medici1579-12-24spaincatherine de medici1580-01-26henri iii1580-02-111580-02-121580-03-03sophycatherine de medici1580-02-06Portugalhenri iii1580-02-11guillaume harbrownhenri iii1580-03-17Ragusahenri iii1580-03-17Queen Elizabethhenri iii1580-03-17
As one can see in the above graph, the topics that are discussed in letters to Catherines de Medici (the queen mother) and Henri III (the king) are slightly different. For instance, Jacques de Germigny discusses the Sultana to Catherine de Medici, but not to Henri III. Important concerns such as Semisi Bassa (the premier vizier, Agmar is a poor rendering of his middle name Semsi Ahmet) and the Spanish are discussed in letters to Henri III and Catherine. In addition, the frequency of those topics are made clear with the dates.

While the above rendering demonstrates the disparity in the topics written about to the King and those written about to his mother. The differences in the frequency with which certain regions are discussed can be displayed in a separate rendering.

catherine de medici
27
catherine de medici
henri iii
38
henri iii
Aleppo
1
Aleppo
Algiers
5
Algiers
Arabia
1
Arabia
black sea
1
black sea
Candia
1
Candia
England
5
England
fez
1
fez
Greece
2
Greece
Istanbul
25
Istanbul
Lepanto
1
Lepanto
Moldavia
2
Moldavia
Perse
3
Perse
Portugal
1
Portugal
Ragusa
1
Ragusa
Spain
11
Spain
Tartary
2
Tartary
Transylvania
1
Transylvania
Wallachia
1
Wallachia
Aga
1
Aga
Agmar premier vizier
1
Agmar premier vizier
Alep
1
Alep
Algiers
1
Algiers
arabie
1
arabie
aymar bassa
2
aymar bassa
Barbary States
2
Barbary States
black sea
1
black sea
Candia
1
Candia
Captain Bassa
2
Captain Bassa
Corsaires
1
Corsaires
England
2
England
English
1
English
fez
1
fez
greece
1
greece
guillaume harbrown
1
guillaume harbrown
Janissaires
1
Janissaires
Joseph Mickes
1
Joseph Mickes
l’armee d’espagne
3
l’armee d’espagne
la sultane femme
2
la sultane femme
Lepanto
1
Lepanto
Mahomet Bassa
4
Mahomet Bassa
mustafa bassa
3
mustafa bassa
osman bassa
1
osman bassa
Perse
2
Perse
Portugal
1
Portugal
Queen Elizabeth
1
Queen Elizabeth
Ragusa
1
Ragusa
Roy d’Algier
1
Roy d’Algier
roy d’espagne
3
roy d’espagne
Rustan Bassa
1
Rustan Bassa
Semisi Bassa
4
Semisi Bassa
sinan bassa
3
sinan bassa
sophy
1
sophy
spain
5
spain
sr. batory
1
sr. batory
tartares
2
tartares
transylvania
1
transylvania
vayvode de Bogdania
1
vayvode de Bogdania
Wallachia
1
Wallachia

In the above visualization, the topics are organized from the most frequently referenced to the least frequently referenced. They are then connected to the region in which they are located. For instance, when the ambassador references Mustafa Bassa, he is concerned with issues in Istanbul, so his topic region (or location) is Istanbul. Or while l’armee d’espaigne was not located in Spain, the topic region/location is Spain because the issue of concern is the power of Spain. Locating the topics within the regions of concern that the topic represents allows me to understand more easily the areas of the world that the French ambassador concerned himself with at the Ottoman Porte as well as what he thought the French king was interested in. What the visualization indicates is that the French ambassador was incredibly concerned with the Spanish. Spain is the most frequent topic, and Spain is the second most frequent region. The most frequent topic location is Istanbul, but that is to be expected since the ambassador is located himself in Istanbul. Also, I should indicate that these are only preliminary results. I am still sorting through some of my manuscripts since the paleography issues have slowed down the process. Also, I should indicate that France does not show up since I intentionally do not track those references since it would be in every single letter.

Palladio’s mapping feature, however, has provided more difficulty in organizing the data. I have clearly made some mistake since the accurate amount of letters referencing Spain never seems to come out right in that feature. I will continue to mess with the organization and combination of connecting tables. I think the mapping feature will be very helpful because the idea in cataloging topics is to get a better understanding of how he thought of the diplomatic playing field that he was expected to participate in and who were the major players. How better to do this that to actually place that network on a map? So, I will keep messing with it.

Networking the topics in an ambassador’s letters (part 1)

For my paper, I am reading the letters of a French ambassador, Jacques de Germigny,  to the Ottoman Empire between 1579 and 1584 and listing all of the proper nouns that he refers to as a means of finding the topics that he was concerned with. Currently, I am reading the letters and placing the proper nouns (for example, Espagne, Aly Aga, etc.) into a spread sheet. I am trying to figure out the best way to format the spread sheet to make the information easier for me to put into RAW. I often have multiple topics per letter, so I figure that the spread sheet will become very long. The paleography of the letters will probably pose some problems, so I may have to not include some letters that I am not fully able to make out or whose encoding are not deciphered. So far I have not had that issue, but I am also not too deep into the manuscript yet, and I know some of the more difficult letters are to come.

My Omeka Exhibit

Beginning to create an online exhibit is rather simple with Omeka. The most time consuming aspect of creating a basic exhibit is through inputting the meta data, which is extensive. However, it ought to be since one is producing the exhibit for others to use the information, and presumably the user of the provided data would like to know from where it came. Some of the meta date in the Dublincore system makes you think about your document in terms of what information should be provided. For example, what information should should one enter to the “identifier” area.  It states that the identifier should be “an unambiguous reference to the resource within a given context,” but what exactly does that mean? This is really the only data set I could not figure out how to fill.

It does not take much playing to learn how to organize various pages and exhibits. One simply builds from the bottom up–adding items, then combining them into collections and exhibits, and adding simple pages to explain what is actually going on in the page. In creating my exhibit, I focused on the complexity of Franco-Ottoman diplomacy. By this, I was trying to demonstrate the multidimensional aspects of French relations with the Ottoman Empire. To do this, I chose documents that had in their root the various issues that surrounded the relationship in the early 1580s–the invitation to Henri II to attend the circumcision of the Sultan’s son, the negotiations of the capitulations, issues of the Persian and Ottoman conflict that always interested the French, as well as letters directly from each monarch to the other. Since this was a fairly straightforward mission, I chose the “Thanks, Roy” theme since it looked the cleanest and provided very little clutter between the viewer and the documents in the exhibit itself.

My goal was to introduce the Franco-Ottoman diplomacy with the documents themselves, so I provided a brief introduction into the complexity the diplomacy and the multiple activities and concerns that went on at the same time. This is followed directly by a page that provides the sources themselves. The one problem I had on this page was being able to change the order in which the documents appeared. I never figured out what I did wrong, but they are not presented in any logical order unfortunately. I would have preferred to order them chronologically, but it was to no avail. Either way, I was able to do much in a short time, I think, because of the general usability of Omeka. My exhibit, admittedly, is fairly boring. I think this is partly due to the fact that I have not generally thought about how to present such historical information  in a manner that privileges the document rather than the analysis of the document. Nevertheless, it is a rather informative process to go through. It truly demonstrates how conditioned some of us have become to following prescribed formulas in how to present historical information.

Mapping the First Michigan Cavalry

Mapping the battles of the First Michigan Cavalry from the beginning of 1864 to the end of the Civil War posed various problems that I had to overcome. Some of these are particular to me. For instance, my lack of familiarity with both Civil War and more importantly the geography of Virginia made recognizing the places at which the battles took place particularly problematic. Places such as “Mallory’s Crossroads” are not easily searched through Google and often return multiple results. While this is a complication that all must overcome, a better familiarity with both topic matters would facilitate more accurate judgments.  I tried to find the coordinates of battles wherever possible in order to be more precise, but once again, this is a pursuit easier said than done. Where this was not possible, I simply leaned on GoogleMaps’s ability to recognize the place for which I was searching. There were a few battle places that I could not find, such as Duguidsville. In these cases, they were simply left off of the map.

When mapping the actual series of battles, the large quantities of battles on a single map provided an added complication. How can one make sense of a map that has forty-two icons representing battles that do not present a clear linearity? In order to make the map more readable, I collected the various battles into groups according to the campaign they were connected to or chronological connections. Thus all the battles that were part of Sheridan’s raid from Winchester share the same icon and icon color. The same goes for the Appomattox courthouse march, Sheridan’s Shenandoah Valley campaign, and the others. Moreover, since the first Michigan cavalry unit did not simply process in a single direct line, but also made numerous turns and back tracked, where the path either stretched over an extensive distance or followed a complicated route, a line is provided (in the same color as the battle icons connected to that particular campaign) to connect provide an aid in recognizing the general route taken by the cavalry unit. Although this provides a multicolored map, hopefully what is loses in eye appeal, it gains in readability.

Visualizing Networks

This week in our Clio wired class, we are using the network analysis tools Gephi, RAW, and Palladio. After perusing Gephi, I think I will avoid the use of it since one must download it, and it seems needlessly complicated in comparison to RAW and Palladio. The construction of multiple excel sheets to produce the same visualizations that Palladio and RAW produces seems to me to be excessive.  Of course, I understand that the extra complication means that Gelphi is probably more manipulable. At the moment, the extra control over Gelphi is not necessary for my current interests. In comparing Palladio and RAW, Palladio seems much more useful for questions that are more interested in the geographic representation of networks since it has only one visualization option outside of the mapping feature: the “graph” feature that can be seen below

.Screenshot (4)

As one can see the graph feature clusters the data sets with those groups they are connected to. It is easy to see that most of the regiments were not involved in the same battles, but there was some crossover, which connect the regiments together in the graph: 136th New York, 44th New York, and 29th New York all participated in the battle of Chancellorsville, for instance. The clustering aspect of the graph, however, makes it tough to actually read the the names of the battles.

RAW Provides more possibilities for visualizing the data. In the circular dendrogram the overlapping regiments participating in various battles are more clearly shown. However, one must sacrifice the ability to view the differences in the quantity of battles that each regiment participated in.

Dallas136th New York InfantryBentonville136th New York InfantryStone Mountain136th New York InfantryAtlanta136th New York InfantryPeach tree Creek136th New York InfantryKenesaw Mountain136th New York InfantryTurner’s Ferry136th New York InfantryCassville136th New York InfantryResaca136th New York InfantryChattanooga136th New York InfantryWauhatchie136th New York InfantryGettysburg136th New York Infantry1st Michigan Cavalry29th New York Infantry44th New York InfantryChancellorsville136th New York Infantry29th New York Infantry44th New York InfantryAverasboro136th New York InfantryHagerstown1st Michigan CavalryOld Church1st Michigan CavalryTrevilian Station1st Michigan Cavalry4th New York CavalryWinchester1st Michigan CavalryFront Royal1st Michigan Cavalry4th New York CavalryShepherdstown1st Michigan Cavalry44th New York InfantrySmithfield1st Michigan Cavalry4th New York CavalryOpequon1st Michigan Cavalry4th New York CavalryCedar Creek1st Michigan CavalryPicket1st Michigan CavalryHawes’s Shop1st Michigan CavalryFive Forks1st Michigan CavalryWillow Springs1st Michigan CavalryBrentsville1st Michigan Cavalry4th New York CavalryFort Scott1st Michigan CavalryMonterey1st Michigan CavalryCold Harbor1st Michigan Cavalry44th New York InfantryFalling Waters1st Michigan CavalryRapidan1st Michigan CavalryRobertson’s River1st Michigan CavalryBrandy Station1st Michigan CavalryCentreville1st Michigan CavalryTodd’s Tavern1st Michigan CavalryBeaver Dam1st Michigan CavalryYellow Tavern1st Michigan CavalryMilford Station1st Michigan CavalryDinwiddle1st Michigan CavalryBull Run29th New York Infantry44th New York Infantry4th New York CavalryCross Keys29th New York Infantry4th New York CavalryGroveton29th New York InfantryFredericksburg44th New York InfantryPiney Branch Church44th New York InfantryWilderness44th New York Infantry4th New York CavalryMine Run44th New York InfantryRappahanock Station44th New York Infantry4th New York CavalryMiddleburg44th New York Infantry4th New York CavalryTotopotomoy44th New York InfantryMalvern Hill44th New York InfantryGaines Mill44th New York InfantryHanover Court House44th New York InfantryYorktown44th New York InfantryLaurel Hill44th New York InfantryBethesda Church44th New York InfantryPetersburg44th New York InfantryWeldon Railroad44th New York InfantryPoplar Springs44th New York InfantryNorth Anna44th New York InfantryBeverly Ford4th New York CavalryNew Creek Station4th New York CavalryStrasburg4th New York CavalryHarrisonburg4th New York CavalryPort Republic4th New York CavalryNew Market4th New York CavalryMiddletown4th New York CavalryLuray4th New York CavalryFairfax Courthouse4th New York CavalryGrove Church4th New York CavalryJefferson4th New York CavalryHartwood Church4th New York CavalryHope Landing4th New York CavalryKelly’s Ford4th New York CavalrySnicker’s Gap4th New York CavalryAldie4th New York CavalryUpperville4th New York CavalryJones Cross Roads4th New York CavalryCulpepper Court House4th New York CavalryRacoon Ford4th New York CavalryRapidan Station4th New York CavalryPiedmont4th New York CavalryBealton Station4th New York CavalryRobertson’s Tavern4th New York CavalryRichmond4th New York CavalryAylett’s4th New York CavalryWhite House4th New York CavalryJones’ Bridge4th New York CavalryCharles City Courthouse4th New York CavalryPrince George Court House4th New York CavalryDeep Bottom4th New York CavalryWhite Post4th New York CavalryBerryville4th New York CavalryCharlestown4th New York CavalryHalltown4th New York CavalryLeetown4th New York CavalryFisher’s Hill4th New York CavalryTom’s Brook4th New York CavalryRood’s Hill4th New York CavalryLiberty Mills4th New York Cavalry

This is just one of the various visualizations that RAW provides. Nevertheless, which program one uses is probably determined by the question that one is hoping these visualizations will contribute to. Adding coordinates to these battles as well as dates could illuminate the overlap between regiments and the battles they participated in over time and space in a way that might help show how the North dealt with logistical concerns in the civil war. This question would probably be better focused toward Palladio that is built for such a mapping project. Although, more data would better demonstrate what network analysis can actually do, these examples provide some suggestions in that direction.

nGram and Text Mining

Using the nGram viewer can provide interesting trends that one might otherwise not expect. Searching the terms “France,” “turcs,” “Ottoman,” “Angleterre” (England), “Espagne” (Spain), “Tyran” (tyrant), and “Allemagne” (Germany) in the Google nGram viewer, searching only French texts between 1500 and 1700.

The nGram produced very interesting results. Between 1550 and 1556, “Turcs” was referenced more than the other countries including France. One would certainly not expect such an increase. Even more interesting, however, is the general increase in the reference to all of the countries between 1567 and 1584. Such an increase is striking because it is in the middle of a particularly caustic domestic crisis in the French Wars of Religion.  One certainly expects an increasing in references to “France” during the domestic crisis, especially since it inspired a movement for wholesale reform within the kingdom during the period. [1] The increase in references to external countries, however, is rather unexpected. Another striking feature of the graph demonstrates that in general the waxing and waning of numerical references to the search terms is that the countries as well as “turcs” tend to flow along with one another–increasing and decreasing at the same periods. One notable difference is that references to “turcs” increases between 1670 and 1675 while references to all other countries are decreasing during that period. Nevertheless, there seems to be an overall interest in foreign countries during the same periods rather than growing and decreasing interest in particular areas at different periods.

Interestingly enough, searching the New York Times nGram viewer, “chronicle,” shows a similar parallel waxing and waning references to foreign states in a much different period in the United States. I searched “Saudi Arabia,” “France,” “England,” “Germany,” and “Turkey.”

Except for the 1860s, when there is an increase in France and England, but not the others. By the 1870s, all the countries except Saudi Arabia begin moving parallel with one another.

Using the text mining tools in Voyant was not quite as productive as I wished. Finding full text searchable texts proved quite difficult (those that lacked a PDF layered in front), especially since the Gallica website had various errors loading texts this week. Thus, I used the seven New York Gettysburg texts. Not being familiar with the documents makes it more difficult to understand what voyant returns. The most interesting features to me are the word trends feature and the keywords in context. Quickly being able to compare the differences in the frequency of a charged word such as “honor” between the different texts can be very illuminating.


As shown above, documents three and four are much more interested in honor than documents one or seven. This might demonstrate differences in the overall concern of the different documents, but if we are interested in how honor was understood in these documents a quick look at the “keywords in context” feature will provide a brief overview of how the documents used honor.

Certainly these are just snippets, but they can provide at least a beginning process of where to search.

[1] Mark Greengrass, Governing Passions: Peace and Reform in the French Kingdom, 1576-1584 (New York: Oxford University Press, 2007)

Citing Eighteenth Century Collections Online in Scholarly Articles

Databases have transformed the way many of us interact with historical sources. How much do we actually cite the databases that we use to find our sources? Are certain disciplines more forthcoming in citing databases used than others? Searching JSTOR for references to the database Eighteenth Century Collections Online  (ECCO) provides some preliminary evidence that historians reference their databses (in this case, ECCO) much less than other disciplines, but historians’ hesitance to cite ECCO is far from exceptional due to the overall lack of such a practice among scholars as a whole.

Admittedly, the research for this investigation was rather rudimentary, but the results are still telling. The results in this post come from a single search for “Eighteenth Century Collections Online” (in quotes) in JSTOR, which returned over 126 results, published between 2007 and 2014. I also searched the term “ECCO,” but it rendered too many results to evaluate. Moreover, the vast majority of the results used the term “ecco” in ways that had nothing to do with the database. Of 126 results, Fifty of the results came from clearly non-historical journals–for example, PMLA, ELH, Huntington Library Quarterly, etc. Of the remaining 80 journals, the vast majority came from interdisciplinary journals, or “studies” journals, such as Eighteenth Century Studies. Focusing on just one journal that is the most frequent result, Eighteenth Century Studies (nine results, or roughly 7% of the total results), we can more easily see the disparity between the literary and historical disciplines in the citations of ECCO. Of the nine results, six are clearly literary [1]; two are explicitly historical [2]; one is a discussion of the limits of ECCO [3]. These numbers suggest that literary scholars are more comfortable with citing the databases with which they work.

Nevertheless, the very small numbers suggest that very few articles actually cite the databases in use. Conservatively estimating an average of five articles per quarterly publication, 140 articles have been published through Eighteenth-Century Studies between 2007 and 2013.  To assume that only nine of those 140 (or 6.5%) actively used ECCO in their research seems to be folly. Historians–from this admittedly limited sampling–seem to be bringing up the rear in what can hardly even be called a trend to cite the databases through which scholars reach their sources.

———————————-

1. Brandy Lain Schillace, “‘Temporary Failure of Mind’: Deja Vu and Epilepsy in Radcliffe’s ‘The Mysteries of Udolpho,'” Eighteenth-Century Studies 42:2 (winter 2009): 273-287;  Mary Helen McMurran, “The New Cosmopolitanism and the Eighteenth Century,” Eighteenth-Century Studies 47:1 (Fall 2013): 19-38; Laura Baudot, “An Air of History: Joseph Wright’s and Robert Boyle’s Air Pump Narratives,” Eighteenth-Century Studies 46:1 (Fall 2012): 1-28; Alex Wetmore, “Sympathy Machines: Men of Feeling and the Automaton,” Eighteenth-Century Studies 43:1 (Fall 2009): 37-54; Ala Alryyes, “War at a Distance: Court-Martial Narratives in the Eighteenth Century,” Eighteenth-Century Studies 41:4 (summer 2008): 525-542; Patrick C. Fleming, “The Rise of the Moral Tale: Children’s Literature, the Novel, and ‘The Governess,'” Eighteenth-Century Studies 46:1 (summer 2013): 463-477; Scott M. Cleary, “Castles in the Air: Christopher Smart and the Concept of System,” Eighteenth-Century Studies 43:2 (winter 2010): 193-206. All accessed through JSTOR.

2. Peter Walmsley, Whigs in Heaven: Elizabeth Rowe’s ‘Friendship in Death,” Eighteenth-Century Studies 44:3 (spring 2011): 315-330; James Chandler, “Edgeworth and the Lunar Enlightenment,” Eighteenth-Century Studies 45:1 (Fall 2011): 87-104. Both accessed through JSTOR.

3. Patrick Spedding, “The New Machine”: Discovering the Limits of ECCO,” Eighteenth-Century Studies 44:4 (summer 2011): 437-453, accessed through JSTOR.

Digitization and OCR

The OCR feature in Google drive provides and very instructive view of the possible limitations in how one searches documents. I converted document P715003  to text, and the results were less than desirable. They improved as I cropped out the borders of the paper to leave only the text, but this only went so far. The text did not always pick up in the line breaks or word breaks in the document. Various markings made by hand found their way into the text as random letters. At one point, “that you talked with in connection” was converted to “that you ta].de 11th in mmnmtiozfs1.” One of the major problems is that the document is slightly slanted. I do not know how to manipulate the document to correct for this, but one may hypothesize that a straightened document would render superior results. That being said, I cannot find any distinct markings in the document that may account for the discrepancy in the above conversion.

The Chronicling America project at the Library of Congress also demonstrates some of the limitations of OCR technologies if they have not been cleaned up by someone. I looked at the Anderson Daily Intelligence, 9 Sept. 1914; Omaha Daily Bee, 9 Sept. 1914; and The Spanish America, 9 Sept. 1914. Many of the problems with the OCR on this project stem from the condition of the paper. The OCR has problems with text that is faded on particular lines or smudges. In such cases one sometimes finds odd characters–a dollar sign for instance. It also has problems with hyphenation. For example, “Von Hinden-burg’s” is converted to “Von Hinden [next line] ‘ v hug’s” in the Omaha Daily Bee (“German Center Gaining Slowly against Allies,” pg.1). This might be especially problematic if someone is searching stories that reference von Hindenburg since this story would clearly not be returned. It is possible that fuzzy logic may still find the story if one takes into account the problems OCR has with hyphenation.

My own research poses more problems most likely because the 16th and 17th century French language poses extra complications on the OCR programs. The most used words that might direct one to documents for my research, “Turc” (and all its variant spellings used at the time), tends to be converted accurately. However, searching for documents that reference particular Ottoman Sultans would be particularly complicated due to spellings, but these tend not to be to problematic if one finds the particular spelling in use. Looking particularly at L’Inventaire Generale de l’Histoire des Turcs by Michel Baudier, one finds that the accuracy is problematic in many areas. In terms of the searchable words that I would use, there are fewer mistakes, unless “Constantinople” ends up hyphenated, or a smudge falls on “Soliman” which is not too often. In sum, for one to find documents that reference issues, one must be aware of the limitations of OCR to account for them.

 

Franco-Ottoman Digital History

The digital history sources/resources on the Franco-Ottoman alliance during the sixteenth century beyond digitized archives remain rather limited. As like so many other areas, Wikipedia holds a prominent place in terms of the secondary digital history. It provides pages on the alliance itself as well as individuals. If one searches “Franco-Ottoman” “French Wars of Religion,” one finds first the Wikipedia page, but also some other sites that: an online book review of Allies with the Infidel by Christine Isom-Verhaaren,  and a statement of research interest. Beyond these useful sites, one finds a plethora of useless websites including the entertaining alt-history sites. A search of “Francois de Noailles,” a French ambassador to the Ottoman court did provide a link to a posted paper on Academia.edu. Possibly the most important non-digitized digital source is a website, hazine.info, on the various online resources that pertain to middle eastern resources. This site provides not just online resources but explanation of all the physical resources available in the archives (both eastern and western archives) as well.

Digitized sources are much more numerous than online encyclopedias, online exhibits, or other digital medium. Gallica.bnf.fr, the French national library’s digital arm, has digitized many sources including a compilation of the correspondence of the French ambassadors in Constantinople (Fonds Francais 161 41-16144). The Venetian archives have some online sources, but their site has proven far less user friendly than Gallica. Luckily, hazine.info has a link to the digitized collection of the most important fonds in the Venetian archives concerning the Ottomans, the Michellanea documenti turchi. These documents are simply posted as links in the website, but they lack any discerning indexing or summaries of what the documents are. Nevertheless, beggars cannot be choosers. At least, they are digitized and available. In total, the available digitized documents far outweigh the other available digital sources.

My Web Presence

After Googling myself, as so many of us do (and as my class had to do for its first practicum), I think my web presence is acceptable, but it could use some work. I learned that having an uncommon name like mine is a double edged sword. On the positive side, I share a web presence with only one other Nathan Michalewicz. So, my Academia.edu page is the first page that comes up in the results. On the negative side, other references to me that are in the prefaces of books or in conference programs were misspelled. They only show up in Google results if one searches “Nathan Michaelwicz.” This negative is somewhat counterbalanced by the frequency that my last name is misspelled. Chances are a prospective employer that Googles me will in all likelihood misspell my name and find those references.

At the very least, this exercise has shown me how woefully outdated my Academia.edu page is. More importantly, I know there is much more that I can do to make my presence on the internet known. My new twitter account will help I’m sure–especially since I have realized that almost every major archive/library that I will use has a twitter account. This website/blog will also help expand my professional brand. Focusing on my web presence, however, has been a little discomforting. I find it a little depressing that one must shamelessly market oneself on the internet in this way. At the same time, this is the world we live in, and the last time I checked, I very much preferred employment over unemployment. So, if this helps me market myself and my research, so be it.